Browse Topic: Control systems

Items (6,116)

Leveraging Domestic Automotive Software Development Best Practices for MOSA and GCIA/Victory Implementation

2026-01-7538

9/22/2026

ISO 26262ISO/SAE 21434ISTQB/ASPICEMOSAGCIAVICTORY

Priemer, Douglas, Sime, Karl

Experimental Comparison Between Real and Simulated Battery Pack Efficiency in Light Quadricycles Using a Custom Inertia Dynamometer

2026-24-0008

9/21/2026

This study compares the energy efficiency of a real battery pack and a simulated battery pack using a hardware-in-the-loop battery emulator, through experimental testing on a dedicated inertia dynamometer for light quadricycles. The investigated LiFePo4 battery pack has a nominal voltage of 48 V and a nominal capacity of 100 Ah. Initial characterization identified a reduced State of Health based on capacity (SOHC), with a measured usable capacity of 48 Ah (from the nominal 100 Ah) and a corresponding reduction in charge acceptance capability. The emulator was configured to replicate the degraded battery characteristics, including the open-circuit voltage (OCV)-SOC relationship, internal resistance, and current limitations, enabling a direct comparison between simulated and experimental dynamic behavior. The experimental setup was designed to overcome the limitations of conventional chassis dynamometers for low-mass, independent four-wheel-drive quadricycles operating without mechanical friction braking systems. Multiple driving cycles were reproduced using a PLC-based closed-loop control system, with data acquisition performed via CAN communication. The comparative analysis highlights significant differences during regenerative braking events. While the emulator accurately reproduces baseline electrical behavior under mild operating conditions, the aged battery exhibits strong limitations during both high-power acceleration and severe deceleration phases. In particular, increased internal resistance and transient electrochemical polarization lead to premature saturation of charge acceptance, resulting in rejection of high-frequency current transients. Consequently, the experimentally observed energy recovery is significantly lower than the theoretical values predicted by the emulator. In addition, due to the absence of mechanical braking, the reduced regenerative capability directly leads to speed tracking deviations, as the required braking torque cannot be fully achieved. These results identify battery degradation as a key physical constraint affecting both energy efficiency and dynamic braking performance, highlighting the importance of improved electro-thermal and aging-aware model calibration for realistic system-level simulations.

Sementa, Paolo, Vaglieco, Bianca Maria, Altieri, Nunzio

EKF-Based Machine Learning Approach for Battery SOH Prediction in Commercial Vehicles Fleet

2026-24-0002

9/21/2026

Estimating battery state of health (SOH) from field data is essential to ensure successful operation and increase the uptime of battery electric vehicles (BEVs). Most studies in the literature propose methods relying on datasets acquired under controlled laboratory conditions. However, SOH estimation becomes significantly more challenging when dealing with real-world data due to the increased variability and complexity of operating conditions. In this work, CAN telematics data, sampled at 1 Hz, were collected over approximately 20 months of operation from 10 electric commercial vehicles. During this period, a maximum battery degradation of 4% is observed within the fleet. Firstly, a model-based framework was introduced, in which a second-order battery equivalent circuit model (ECM) was coupled with an extended Kalman filter (EKF) to estimate the battery SOH. Results confirmed that the EKF is able to accurately capture the battery's physical behavior and degradation trend, yielding a maximum root mean square error (RMSE) of 1.23% when compared with the SOH signal provided by the onboard BMS. However, a Kalman filter requires accurate model parameter identification and high-frequency measurement data, leading to increased computational costs. To bridge these gaps, this paper utilizes the SOH estimates obtained from the EKF to train and validate a feedforward neural network (FNN) model, specifically designed to operate on aggregated metrics. The FNN model can provide accurate SOH estimates, with a RMSE as low as 0.26% during the testing phase. The approach proposed in this work combines the interpretability of model-based methods with the scalability and reduced data dimensionality of machine learning (ML) ones, making it more suitable for monitoring battery SOH in large fleets of BEVs.

D'Agostino, Valerio, Pulvirenti, Luca, Shanker, Anirudh, Cardone, Massimo, Rizzoni, Giorgio, Vitale, Francesco

Design and Analysis on a Traction-type Power-assisted Follow-up Vehicle for Emergency Rescue

2026-99-1547

9/11/2026

To address problems in China’s emergency rescue scenarios—such as limited functionality, insufficient mobility, poor adaptability to complex terrain, the labor-intensive nature of manual carrying, and the lack of flexibility of fully automatic carts—a traction-type emergency rescue power-assisted follow-up vehicle was designed and developed. With the core design goals of “lightweight, high mobility, and human-machine collaboration”, this power-assisted follow-up vehicle has multiple advantages. At the structural level, it supports rapid folding and unfolding, enabling convenient operation and adaptation to transportation needs in various emergency rescue scenarios. In terms of material selection, it balances strength and lightweight properties, and its key components possess anti-cutting and flame-retardant capabilities, allowing adaptation to the harsh environment of emergency rescue. The power system adopts modular replaceable batteries and is equipped with a high-performance control unit, motor, and shock-absorbing suspension design. This enables normal operation in a variety of complex terrains. The control system is centered on human-machine collaboration. It features simple operation and automatic adjustment of operating status, effectively reducing the operational burden and physical exertion of rescuers. Meanwhile, it supports the master-slave expansion function, allowing flexible switching from a two-wheel structure to a four-wheel structure to meet diverse rescue needs such as material transportation and casualty transfer. This power-assisted follow-up vehicle can effectively solve the material transportation problem in the “last few kilometers” of emergency rescue.

Xu, Jiang, Hou, Yumeng, Yang, Han

Design and Research of Large-Tire Replacement Robots

2026-99-1127

9/11/2026

In view of the large volume and weight of the tires of mining dump trucks and the difficulty in replacing them, a large tire replacement robot is proposed based on the tire parameters and the tire replacement process. The overall research scheme for the robot was developed using the functional analysis method, and the functional element solution and combination were completed. Based on the best solution obtained, a three-dimensional model of the tire changing robot was established using the SolidWorks software, followed by control system design and workflow analysis. To investigate the robot's operational kinematics, a simulation was conducted in the SolidWorks Motion module. The motion curve of the flipping platform during its operational state was obtained. A finite element simulation of the robot's front support beam was performed using ANSYS Workbench to obtain its stress and deformation contours under both no-load and heavy-load conditions. The structural parameters of the front support beam were optimized, focusing on its mechanical characteristics under heavy-load conditions, and the response surfaces of different parameters were obtained. The optimization yielded a 9.599 kg reduction in the mass of the front support beam. The maximum stress of the grasping mechanism under static simulation analysis is 50.617 MPa, with the maximum deformation of 0.4221 mm occurring at the end of the mechanical hand. Ground contact simulation for the robot's walking tires was conducted with Abaqus. Employing the Mooney-Rivlin hyperelastic model, this study investigated the mechanical response of the tire to static and dynamic loading, leading to the identification of the optimal operational load. The simulation results show that there is no interference among the various mechanisms of the large tire changing robot during operation. It can quickly complete the tire installation and removal tasks with precise control, and its strength and rigidity meet the requirements. This verifies the rationality and feasibility of the robot. The research on the large tire changing robot can provide a new approach for the maintenance of large transport vehicles such as mining dump trucks.

Tian, Liyong, Zhang, Haijian

Adaptive MPC Path Tracking Control for Autonomous Vehicles

2026-99-1570

9/11/2026

This work introduces a Model Predictive Control (MPC) path tracking controller, which is developed to boost robustness, tracking precision, and vehicle stability when navigating high-speed and high-curvature driving scenarios. First, a 3-degree-of-freedom (3-DOF) dynamic model of the vehicle is established to serve as a reference. Next, a linear time-varying MPC control algorithm is formulated, with constraints on yaw rate, lateral velocity, and road boundary conditions taken into account; a comprehensive performance metric that balances tracking accuracy and control smoothness is also defined. Third, the time-domain parameters of the MPC framework are optimized using an improved genetic algorithm. Finally, the effectiveness and accuracy of the proposed controller are validated via co-simulation experiments conducted on the Matlab/Simulink and Carsim platforms. Simulation results demonstrate that the controller exhibits excellent robustness: the peak lateral tracking error is only 0.05 m on high-friction roads and 0.12 m on low-friction roads, with a maximum heading error of 0.15°. Additionally, the vehicle’s dynamic stability is notably enhanced: the yaw rate is reduced by 9.6% and 15.7% on high- and low-adhesion roads, respectively, while the sideslip angle is decreased by 13.2% and 18.4% under the same conditions.

Yu, Hanzhengnan, Hou, Xiaoyi, Zhang, Hao, Zhou, Weichen, Liu, Yu

Train Delay Reduction Approach based on a Virtually Coupled Trains Following Model with Timetable Recovery Process: A Case of High-Speed Rail

2026-99-1516

9/11/2026

One challenge in railway operation is how to achieve high levels of punctuality and reliability. However, especially in peak hour operation, a high volume of train traffic will affect timetables, which are more sensitive to the increase in travel time. The concept of virtual coupling has been introduced for controlling train movement mainly to increase capacity. As the operation under virtual coupling requires a short separation distance between trains, it might be applied to reduce the delay and recover the train timetable. However, there is no approach proposed detailing how the coupling is applied to reduce delay. In this paper, the virtual coupling state movement approach based on a vehicle following model with the coupling conditions determined to couple a group of trains for reducing or preventing secondary delay is proposed. The train operation under the proposed approach is simulated in MATLAB software, then applied to the hypothetical case, High-speed line, Bangkok - Nakhon Ratchasima, Thailand. The delay analysis is performed, and the waiting probability is determined to prove the effectiveness of the proposed approach. The simulation results show that trains will be virtually coupled with their front train as a form of train convoy when they cannot proceed at the ideal speed. Thus, operating train movement based on the proposed approach can reduce secondary delay and bring a train to arrive on time compared to the operation under the moving block control.

Chansong, Sukanya, Ketphat, Naphat

Trajectory Tracking Control for UUVs Based on Deep Reinforcement Learning

2026-99-1132

9/11/2026

Unmanned Underwater Vehicles (UUVs) operate in complex and uncertain environments, which require a suitable controller. While traditional PID controllers are widely used, they often have slow response speed and inadequate disturbance rejection, particularly under complex and uncertain conditions. To overcome these shortcomings, this paper introduces the DDPG-DLPID, an adaptive motion controller, including a Deep Deterministic Policy Gradient (DDPG) reinforcement learning that can acquire the parameters of PID controllers. In this paper, we design two loops: the inner loop handles velocity regulation, and the outer loop handles position and attitude. By using DDPG, the system can efficiently adjust the PID parameters of both loops in real time, allowing it to effectively adapt to environmental changes and achieve optimized requirements. To evaluate the controller, we design the following scenarios, including straight-line and complex path-following tasks. Compared with single-loop PID and dual-loop PID controllers, the proposed DDPGDLPID approach achieves faster response and higher tracking accuracy, while substantially reducing tracking errors under interference conditions. Physical experiments under three conditions-straight-line voyage, attitude maintaining, and depth control-were further carried out to validate the strategy’s real-world applicability. Experimental data confirm that DDPG-DLPID has better performance when compared with both traditional PID and dual-loop PID controllers across all test scenarios.

Wang, Ling, Shi, Yan

Study on Longitudinal Vehicle Control Strategy Considering the Speed Reference Trajectory

2026-99-1135

9/11/2026

To ensure the dynamic characteristics in the vehicle’s longitudinal control process, a longitudinal control strategy considering the speed reference trajectory is designed. Based on a hierarchical control method, the speed input in the upper-level control algorithm is designed using a reference trajectory, and the model predictive control (MPC) algorithm is applied to solve for the vehicle’s desired acceleration. In the lower-level control, a feedforward and feedback control structure is used to track the target acceleration, while an inverse longitudinal model is established to calculate the vehicle actuator outputs. Finally, simulation verification is carried out for host vehicle speed change and cut-in, cut-out situations ahead of the vehicle. The results indicate that the method achieves a smoother acceleration response, ensuring driving comfort.

Song, Jia, Li, Wenjie, Ma, Wenyu

Application Layer - Diagnostics

J1939-73_202609 (Current)

9/9/2026

SAE J1939-73 defines the SAE J1939 messages to accomplish diagnostic services and identifies the diagnostic connector to be used for the vehicle service tool interface. Diagnostic messages (DMs) provide the utility needed when the vehicle is being repaired. Diagnostic messages are also used during vehicle operation by the networked ECUs to allow them to report diagnostic information and self-compensate as appropriate, based on information received. Diagnostic messages include services such as periodically broadcasting active diagnostic trouble codes, identifying operator diagnostic lamp status, reading or clearing diagnostic trouble codes, reading or writing ECU memory, providing a security function, stopping/starting message broadcasts, reporting diagnostic readiness, monitoring engine parametric data, etc. California-, EPA-, or EU-regulated OBD requirements are satisfied with a subset of the specified connector and the defined messages.

Truck and Bus Control and Communications Network Committee

High-Precision Micro-Satellite Attitude Control: Design and Testing of an Ultrasonic Motor-Driven Control Moment Gyroscope

2026-99-1291

9/4/2026

The issues associated with the traditional single-gimbal control moment gyroscope (SGCMG) driven by electromagnetic motors, such as complex structure, significant gear backlash, weak anti- interference capability, poor adaptability to space environments, and large volume and weight, make it difficult to meet the attitude control requirements of micro/nano satellites. To address these issues, this paper proposes an SGCMG design based on a rotary traveling wave ultrasonic motor (RTWUM) drive. Ultrasonic motors offer advantages including high torque, fast response, self-locking upon power-off, immunity to electromagnetic interference, and simple structure, making them suitable for spacecraft attitude control systems. This paper elaborates on the working principle and structural design of the ultrasonic motor, covering the entire process from stator modal optimization, flywheel and gimbal structural design to system integration and control system implementation. Through finite element analysis and experimental verification, the designed ultrasonic motor-driven SGCMG meets the requirements of micro/nano satellites in terms of output torque, speed control accuracy, and structural compactness, demonstrating the promising application prospects of ultrasonic motors in aerospace attitude control.

Wu, Jintao, Zhang, Jiyang, Li, Huafeng, Pan, Song

Comparison of Two Distinct Automatic Emergency Braking Control Strategies for Heavy Vehicles

02-20-01-0004

9/2/2026

Research on automatic emergency braking (AEB) control algorithms for heavy vehicles is relatively limited. Compared with passenger cars, heavy vehicle AEB algorithms must accommodate both unloaded and fully loaded conditions, with the latter posing higher demands. This study compares two distinct AEB control strategies: the time-to-collision (TTC) algorithm and the professional driver fitted (PDF) algorithm. Using simulation analyses under three regulatory-recommended scenarios—stationary lead vehicle, slow-moving lead vehicle, and decelerating lead vehicle—the results indicate that the PDF-based control system better adapts to both unloaded and fully loaded conditions. It demonstrates significant improvements in braking performance and robustness compared to the TTC-based system. For an unloaded vehicle equipped with the PDF–AEB control system (5500 kg), the final gap to the lead vehicle is the longest (11.5 m) under the scenario of a stationary lead vehicle with an initial ego vehicle speed of 80 km/h and the shortest (3.1 m) under the scenario of a lead vehicle with an initial speed of 50 km/h braking at 0.4 g. For a fully loaded vehicle (12,500 kg), the corresponding final gaps to the lead vehicle are 11.2 m and 2.5 m, respectively.

Lai, Fei, Huang, Chaoqun

Development of Remote Cab Controller for Construction Machinery

14-15-03-0017

8/27/2026

This article focuses on the research and development of a remote cab controller for pure electric loaders, aiming to address the threats posed by traditional loaders operating in harsh and hazardous environments to drivers’ health and safety. First, the functional requirements of the controller were analyzed, based on which the hardware design with a multicore microprocessor as the core was completed, featuring functions such as signal acquisition, controller area network (CAN) communication, and H-bridge driving. On this basis, a control algorithm framework for remote driving was developed, including modules for signal input, analysis and processing, and signal output. Detailed control strategies were formulated for key components: For the pedal sensor, algorithms for opening degree calculation, automatic zero-position calibration, and dual-signal redundant fault diagnosis were proposed; for the steering module, precise angle calculation and force feedback feel simulation were achieved; and for the electric control handle, a hysteresis control algorithm was developed to suppress shocks caused by overly fast operations. In addition, a hierarchical fault diagnosis mechanism was established to ensure system safety. To verify the controller performance, a complete remote driving system was built. Field test results show that the system exhibits good signal following and control responsiveness in terms of traveling and working functions. Efficiency tests indicate that the remote driving efficiency can reach 80% of that of in-person operation under short-term test conditions, demonstrating the technical feasibility and control effectiveness of the developed controller. While the prototype exhibits promising performance for pilot deployment, long-term reliability metrics such as mean time between failures (MTBF) remain to be validated through extended field operation.

Lu, Yueqi, Ji, Shaobo, Yu, Qiuye, Li, Meng, Xu, Haozhi, An, Meng

Delay-Compensated Active Anti-Roll Bar of Tractor-Trailers Using Two-Dimensional Piston Pump Electro-Hydrostatic Actuators

02-19-04-0027

8/5/2026

As tractor-trailers are essential to global logistics, their roll stability during emergency maneuvers is a critical safety concern. This paper presents a novel delay-compensated active roll control strategy for tractor-trailers using a two-dimensional piston pump electro-hydrostatic actuator (EHA). Unlike existing advanced strategies that assume ideal actuator behavior, this approach specifically targets the inherent response delay in high-tonnage applications. A detailed EHA model, including pump flow characteristics and hydraulic mechanics, was developed and validated through step response experiments. A seven-degree-of-freedom vehicle dynamics model and a model predictive controller were also constructed to compute the required anti-roll moment under emergency driving conditions. In order to address the EHA actuator’s response delay, a delay feedforward controller (DFC) was designed, integrating acceleration feedforward, feedback regulation, and delay disturbance estimation. TruckSim–Simulink co-simulations under double lane-change (DLC) maneuvers at 40 km/h, 60 km/h, and 80 km/h show that DFC improves displacement tracking and reduces peak trailer roll angle by up to 15% compared to a velocity-feedforward proportional-integral-derivative (VFPID) controller. It also enhances control efficiency, as evidenced by lower average motor speeds and pressure response of EHA. The system demonstrates high power-to-weight ratio and efficient tracking capabilities under dynamic conditions. Although active control provides limited benefit at low speeds, the proposed strategy effectively improves roll stability and driving safety under dynamic conditions.

Chen, Lijie, Yin, Yuming, Zeng, Yuhang, Ruan, Jian, Li, Hangqi, Sun, Peng

Comfort Study of Air Suspension System Based on MPC Control

2026-99-0136

7/31/2026

Air springs are increasingly replacing traditional shock absorbers in vehicle suspension systems due to their superior mechanical properties, including adjustable stiffness, nonlinear characteristics, and excellent damping performance. To further explore the potential of air suspension in improving ride comfort, this paper focuses on air suspension. We first conducted mechanical characteristic experiments on air springs to obtain their stiffness and damping characteristics under different inflation pressures and excitation frequencies. These tests provide essential mechanical parameters for subsequent modeling and simulation. Based on the experimental data, a simplified 1/4 air suspension simulation model is constructed, taking into account the nonlinear stiffness and damping properties of the air springs. To simulate real-world driving conditions, a random road surface model is introduced as the excitation input. Simulation analysis is conducted to compare the air suspension system with the traditional passive suspension system. The results indicate that, compared to the passive suspension system, the air suspension system integrated with Model Predictive Control(MPC) significantly reduces key performance indicators, including suspension deflection, wheel dynamic load, and sprung mass vertical acceleration. This indicates that the suspension with model predictive control can effectively suppress vehicle vibrations, thereby enhancing ride comfort and driving stability. The results of this study provide an important basis for the optimal design of air suspension systems and have practical application value for improving the suspension performance of the vehicle.

Yin, Zhi

Design and Development of a Durability Test Device for the Surface of Elderly-Friendly Mattresses

2026-99-0139

7/31/2026

A test device for detecting the durability of the surface of elderly-friendly mattresses was designed and developed, which has functions such as force value monitoring, displacement monitoring, data recording, and hardness grade determination. Through the collaborative work of the mechanical system and the control system, high-precision reciprocating rolling tests and hardness grade determination on the mattress surface are realized. The verification test results show that the relative standard deviation (RSD) value of the mattress hardness grade test results is less than 10%, indicating that the detection data obtained by using this device is stable, meets the design requirements, and has operability.

Wang, Jin, Feng, Panpan, Shen, Guofeng, Zhang, Lei

The Design of an Adaptive Multi-Material Fully Automated Grinding and Polishing Machine

2026-99-0127

7/31/2026

With the increasing demand for material microimaging analysis, there is a growing need for advanced precision grinding and polishing equipment, especially for metals, ceramics, and composites. Existing automated systems struggle with handling complex material challenges. This paper presents a fully automated adaptive grinding and polishing machine based on an STM32 microcontroller that handles multi-material samples. The system includes modules for sample access, cleaning, pad replacement, human-computer interaction, and equipment communication. The STM32 microcontroller executes grinding and polishing tasks based on instructions from the host computer while dynamically adjusting PID control parameters using an improved weighted average optimization algorithm. This approach enhances control accuracy, stability, and overall surface treatment quality compared to traditional PID control methods.

Zhang, Longqing, Kong, Xiangyu, Zhao, Xiuyang, Li, Xingbei

Design and Experiment of a Stable Seed Supply Control System for an Elevating Type Sugarcane Seed Supply Device

2026-99-0819

7/30/2026

Aiming at the problems of seed cane pile-up and unstable seed supply efficiency in the sugarcane seed production line caused by the seed supply device, a stable seed supply control system was designed, which consists of a seed collection box, an elastic seed-clearing plate and an electrical control system, etc. The EDEM-RecurDyn coupling simulation was adopted to analyze the seed supply process, and the optimal elastic seed-clearing plate structure was designed. Using the single factor test and Box–Behnken experimental design analyzed the effects of the seed supply belt speed, the speed of the first conveyor belt, the number of sugarcane seeds in the collection box and the seed cutting efficiency on the supply efficiency. Establish a quadratic regression model for the efficiency of seed supply and determine the optimal parameter combination: the seed supply belt speed of 0.097 m/s, first conveyor belt speed of 1.639 m/s, and the number of sugarcane seeds is 14. Using the number of sugarcane seeds as the input quantity for the controller, the real-time data is fed back by the TOF sensor. The controller automatically adjusts the seed-cutting efficiency to maintain the continuity and stability of the seed supply process of the seed supply device. The test results show that after applying this system, the seed supply efficiency reached 1.77 setts/s, which was 6% higher than that of the fixed-parameter system. This research can provide technical support for the stable seed supply of integrated equipment for sugarcane seed production.

Li, Shangping, Xu, Hechang, Ouyang, Runhong, Li, Kaihua

Design and Verification of Underactuated Coupled-Commutation Omnidirectional Mobile Integrated Camping Robot Chassis

2026-99-0820

7/30/2026

To solve the poor mobility of traditional camping vehicle chassis in complex terrains and confined spaces, this paper proposes an underactuated omnidirectional mobile chassis for outdoor camping vehicles. The chassis adopts a coupled commutation mechanism (double-crank elastic special-shaped connecting rods cross sliders), allowing each wheel to realize two motion modes (omnidirectional translation, in-situ rotation) with just one drive motor, reducing system complexity and cost. A control system based on the RoboMaster Development Board C Type integrates PID angle-loop control and motor speed-current dual closed-loop control for motion stability. Kinematic models for these two modes are established to derive the wheel parameter-chassis motion relationship. MATLAB R2023b-ADAMS 2024 co-simulations show the chassis maintains attitude stability under S-shaped curve, circular curve, and in-situ rotation; Qualisys 3D motion capture experiments confirm its stable attitude in omnidirectional movement.

Ren, Yulong, Lu, Zhiguo, Yang, Dongsheng, Wu, Di, Zhang, Tianyu, Qian, Zhenxin

Research on Multi-Physical Field Accelerated Life Test for Long-Life Rotary Mechanism for Space Applications

2026-99-0814

7/30/2026

The coupled multi-physical field environment in space, including vacuum, high-low temperature cycles, and temperature gradients, is the key factor affecting the life of the spacecraft’s rotary mechanism. Aiming at the use requirements of long-life space rotary mechanisms, this paper designs a multi-physical field accelerated life test scheme. This scheme simulates the vacuum environment, high-low temperature cycles, and temperature gradient conditions encountered during on-orbit operation. Ground-based accelerated life tests were conducted based on this scheme to verify the life of the mechanism under a comprehensive environment. Taking a certain type of space rotary mechanism as the test object, an integrated test platform was constructed, incorporating a vacuum simulation system, a temperature gradient control system, and a mechanism performance test system. Corresponding test procedures and failure criteria were established. Test results verified that after accumulating 130,000 ±7° small-angle reciprocating swings, the mechanism’s lifespan indicators met expectations. Post-test, the overall performance of the mechanism still satisfied the design requirements, with key moving components remaining in good condition. This study provides important experimental evidence for the on-orbit application of this mechanism type and offers valuable engineering reference for the design and evaluation of life tests for space mechanisms under multi-physical field coupling conditions.

Wang, Haomiao, Du, Yuefei, Huang, Mengzhe, Yang, Jinping

Accurate Control of Refueling Volume for a New Type of Oil Change Device in the Reducer of Tobacco Machinery Equipment

2026-99-1618

7/24/2026

In order to achieve precise control of refueling volume, improve oil change efficiency, reduce oil pollution and waste, a new oil change device for the reducer of the range hood equipment is studied. We design a new oil change device that integrates oil discharge and refueling functions based on the operating characteristics of the reducer in the range hood equipment. Using the rotational speed of the power pump and the flow rate of the oil pipeline as variables, we determine the refueling flow rate using a one-dimensional quadratic formula. Based on direct control theory, we optimize the relative position parameters of each component of the device, establish a control matrix, and achieve precise control. The experimental results show that the new oil change device exhibits good performance during both one-time oil discharge and refueling processes, meeting the precise control standards for refueling volume. The design and application of a new oil change device can effectively improve the efficiency and accuracy of oil change in the reducer of the range hood equipment, and have practical application value.

He, Pengtao, Wei, Bo, Liang, Zhiyuan, Deng, Weiren, Liang, Wenbin, Xing, Yuquan

Analysis and Experimental Research on The Impact of the BangBang Valve Switch on the Flow Rate of the Storage and Supply System

2026-99-1615

7/24/2026

This article focuses on a wide range of high-precision storage and supply systems. Under the rated flow rate of 2.928 mg / s of the proportional flow controller, the instantaneous flow fluctuation range of the BangBang valve reaches 2.963 mg / s, exceeding the control accuracy requirement of 1% for the proportional flow controller. By establishing mathematical models of the BangBang valve, proportional valve, and proportional flow controller for simulation analysis, the trend of the simulation results is consistent with the experimental results. Furthermore, considering the spatial layout and weight of the storage and supply system, this paper proposes a method to improve the accuracy of flow output by adding 180 mL of air capacity between the proportional valve and the proportional flow controller. Ultimately, the maximum flow fluctuation of the proportional flow controller at the moment of the BangBang valve opening and closing is 2.941 mg / s, which meets the control accuracy of the proportional flow controller. Moreover, the error between the output flow rate of the proportional flow controller and the rated working flow rate is minor after increasing the air capacity.

Li, Zhong, Li, Zongliang, Yan, Zelong, Huang, Tiankun

Coupled Lateral–Longitudinal Trajectory Tracking Control for Autonomous Vehicles Based on Multi-Agent Reinforcement Learning

12-09-03-0024

7/23/2026

Trajectory tracking control serves as the core operational component of autonomous vehicles, directly determining driving safety and passenger comfort by ensuring control precision and stability. To enhance the tracking accuracy and stability for autonomous vehicles, this study proposes a coupled lateral–longitudinal trajectory tracking controller based on multi-agent reinforcement learning. The framework first establishes a Model predictive controller (MPC) derived from vehicle dynamics, formulating the lateral control process as a Markov decision process. A reward function incorporating lateral error, heading error, and steering angle is designed, followed by the construction of a Deep Q-Network (DQN) Agent to optimize the prediction horizon of the MPC. Subsequently, a position–velocity dual-loop PID controller is developed for longitudinal control, with its parameter optimization strategy learned through a Deep Deterministic Policy Gradient (DDPG) Agent. The Extended State Observer (ESO) is incorporated to perform steering angle compensation for internal modeling errors and external disturbances. Co-simulation experiments are conducted in CarSim and MATLAB/Simulink, and the results demonstrate that the coupled controller achieves superior tracking accuracy and stability in both overtaking and lane-changing scenarios compared with the decoupled controller.

Kun, Feng, Jinxiang, Zhai, Li, Wenli

Research on Clustering Data-Driven Intelligent Perception Algorithm for Micro Mobile Robots

2026-99-1843

7/17/2026

To address the challenges faced by micro flapping-wing flying robots in visual navigation—specifically, the large volume of visual information and the difficulty in transforming it into usable intelligent visual data—this paper proposes a clustering-based data-driven approach for directional and image perception. The aim is to enable intelligent visual navigation for flapping-wing robots. The proposed method performs clustering analysis on gyroscope data from the flapping-wing robot to extract directional features. Simultaneously, it applies clustering techniques to visual images captured by the robot to identify intelligent features such as edges. This approach enables the robot to acquire multiple optimized perceptual data types, thereby enhancing the behavior control system. Through the use of clustering analysis, the method not only improves the effectiveness of visual navigation but also extracts features related to visual targets and environmental information, providing technical support for visual target tracking. The experimental platform consists of a flapping-wing robot equipped with an onboard camera, and the proposed clustering-driven visual image perception approach has been experimentally validated. Experimental results demonstrate the high feasibility and effectiveness of the method in practical applications. The main contributions of this study lie in two aspects: (1) a clustering-driven visual image perception method for flapping-wing robots, and (2) a clustering-based approach for identifying posture and behavioral patterns of flapping-wing flying robots.

Li, Zixuan, Ding, Wei, Zhang, Feng, Song, Min, Liu, Zhaoming, Miao, Lei, Liu, Haotian, Bai, Ning, Tian, Shen, Cui, Long, Wang, Hongwei

Optimization of the Light Environment for the Remote Control Tower Humancomputer Interaction Interface Based on Ergonomics

2026-99-1847

7/17/2026

The development of remote tower systems in aviation and the resurgence of multi-display interfaces and virtual environments have dramatically influenced ATC, increasing both controllers’ visual demands and their ergonomic needs. This study uses the Visual Ergonomics to study the impact of screen luminance level, along with color temperature, on trainees’ visual performance, fatigue, and physical discomfort in the control rooms of the Remote Tower. By combining a simulated remote control system with spectrometer measurements, PVT alertness tests, VMT (Visual Memory Test) measurements, and subjective evaluations, COST B21 can build up a multi-dimensional ergonomic assessment framework. Eight levels of display luminance (and color temperature) were tested, including two illuminance levels (300 lx and 400 lx) and four color temperature ranges (6000 K–9000 K). Using the Analytic Hierarchy Process (AHP), these parameters were assigned weights to derive a Visual Ergonomics (VE) scoring model, and the ideal visual performance was observed at 400 lx illuminance and 8000 K CCT. The results clearly illustrate the significant impact of display parameters on operational performance in remote tower systems and provide both practical data and a theoretical basis for the human factors design and fatigue reduction research on RTSs.

Zhong, Linfeng, Hu, Ruohui, Luo, Peilin, Zuo, Qinghai, Zhong, Qingwei, Ai, Yi

Research on Quadrotor Trajectory Tracking Based on Model Predictive Control

2026-99-1850

7/17/2026

Quadrotors (UAVs) are widely used in intelligent inspection, environmental monitoring, and logistics due to their simple structure, strong maneuverability, and vertical take-off and landing capabilities. However, their highly nonlinear, strongly coupled, and highly constrained dynamic characteristics make trajectory tracking control a challenging task. To improve trajectory tracking accuracy and control robustness, this paper proposes a quadrotor trajectory tracking method based on model predictive control (MPC). First, a six-degree-of-freedom dynamic model of the quadrotor is established and linearized with small disturbances to transform it into a state-space model suitable for MPC design. An MPC optimization controller is then constructed, with an objective function that minimizes state error and imposes an input energy penalty, while explicitly considering the system's input and state constraints. Simulation results demonstrate that this method exhibits good tracking accuracy and control smoothness for typical trajectory tracking tasks (such as circular and spiral trajectory tracking). Compared with traditional PID and LQR controllers, the proposed method significantly improves maximum error, mean square error, and interference rejection. This study provides an engineering-feasible optimization control framework for UAV trajectory control.

Peng, Fei, Tao, Zhong, Gao, Qiang, Jia, Bobo

Attitude Control of a Variant Flying Wing UAV Based on L1 Adaptive and Fuzzy Clustering

2026-99-1858

7/17/2026

This study presents a full-envelope attitude-stabilisation and trajectory-tracking strategy for morphing flying-wing UAVs operating in highly nonlinear and strongly coupled conditions. The approach integrates fuzzy C-means (FCM) envelope partitioning with L1 adaptive control. Small-disturbance linear models are first generated at multiple altitude–Mach trim points; the FCM algorithm then performs unsupervised clustering in the state space, yielding representative subintervals that capture local flight-dynamic characteristics. The optimal cluster number and fuzziness exponent are selected using the partition coefficient, partition index, partition entropy, and Xie–Beni indices. For each sub-interval, an LQR baseline controller is designed and augmented by an L1 adaptive compensator, where a low-pass filter decouples adaptation from robustness to guarantee specified transient-performance bounds under matched/unmatched uncertainties, actuator saturation, and external disturbances. A feed-forward pre-filter realises online decoupling of the multi-input multi-output channels, thereby enhancing adaptability to variable sweep angles and large aerodynamic variations. Simulations covering low-speed/small-sweep and high-speed/large-sweep scenarios demonstrate that the proposed method sustains robust stability across the clustered envelope, outperforming conventional control schemes and confirming its engineering applicability.

Tang, Longhao, Sun, Xiaoxu, Liu, Changlin

A Review of UAV Support Technologies for Low-Altitude Airspace Operation and Management

2026-99-0597

7/10/2026

In recent years, with the low-altitude economy developing rapidly, the operation and management of low-altitude airspace has gradually become a hot topic. Unmanned aerial vehicles (UAVs) constitute a fundamental component of the low-altitude airspace ecosystem, significantly influencing its structure and functionality. The technological advancement of UAVs has fundamentally transformed the operational paradigm for low-altitude airspace management. This paper presents a comprehensive review of UAV-supported technologies in the context of low-altitude airspace operations and management. It systematically analyzes key technologies and applications of UAVs in areas such as airspace capacity and safety assessment, trajectory planning, and standardized flight management. Drawing from kinematic analysis and traffic flow theory, UAV density control and collision risk prediction offer quantitative insights into airspace capacity evaluation. Additionally, probabilistic analysis and simulation techniques enhance the accuracy and efficiency of safety assessments. In trajectory planning, multi-objective optimization algorithms tailored to operational scenarios—such as logistics delivery and agricultural operations—have significantly improved the utilization of airspace resources. Concurrently, collision avoidance techniques leveraging graph search, numerical optimization, and machine learning ensure flight safety in complex environments. Standardized flight management relies on pilot qualification review, airworthiness certification, and planning standardization, while discussing airspace segmentation strategies based on geofencing and intelligent control systems. Future developments in UAV-supported technologies are expected to trend toward higher precision, intelligence, and regulatory integration. By incorporating cutting-edge fields such as deep reinforcement learning and digital integration, these technologies are poised to further enhance the efficiency and safety of low-altitude airspace management, thereby providing robust technical support for the sustainable growth of the low-altitude economy.

Gong, Lei, Ma, Zhenxiao, Luo, Qin

Research on Battery Environment Heat Dissipation Control System

2026-99-0535

7/10/2026

Batteries generate a large amount of heat during operation, and if it cannot be dissipated in a timely and effective manner, it will seriously affect the performance, lifespan, and even safety of the battery. Therefore, battery heat dissipation has become a key challenge in the development of new energy vehicles. The traditional liquid cooling system has problems such as complex design and control, and the need to improve heat dissipation efficiency. To address these issues, this study proposes an optimized design scheme for battery environment heat dissipation control system based on liquid cooling heat dissipation system. This study first conducted an in-depth analysis of the thermal generation mechanism of lithium-ion batteries and studied existing examples of thermal management schemes. On this basis, an innovative forward and reverse circulation device was designed, combined with a liquid cooling heat dissipation structure. The Keil uVision4 programming software was used to write the microcontroller control program, and the circuit was simulated and verified using Proteus simulation software. This study established an experimental platform and conducted physical testing and thermal imaging detection. By collecting temperature change data under different heat dissipation modes and analyzing the experimental data, the results show that the optimized liquid cooling heat dissipation system significantly improves the heat dissipation efficiency. The system exhibits good performance under different cooling modes.

Ding, Xvqiang, Ni, Yiwei, Gu, Chen, Zhang, Jin, Chen, Mingyang, Jiao, Yunxiao

Design of a Quadrotor UAV Controller Based on Fractional-Order Sliding Mode

2026-99-0585

7/10/2026

Aiming at the problems of model uncertainty, external disturbances and high-frequency chattering of traditional sliding mode control in complex working conditions for quadrotor unmanned aerial vehicles, this paper proposes a control strategy based on fractional-order sliding mode. The quadrotor UAV control system has problems such as parameter uncertainty, multi-input multi-output, and sensitivity to internal and external disturbances. Traditional PID control has certain limitations. Sliding mode control has the advantages of strong robustness and simple implementation. Fractional-order calculus has hereditary and memory properties. The combination of the two has better control performance for nonlinear systems. To further improve the trajectory tracking performance of quadrotor UAVs, a fractional-order sliding mode controller is designed based on fractional-order theory and traditional sliding mode control. Finally, multiple experiments are conducted in Matlab/Simulink, including trajectory tracking, parameter perturbation, and anti-interference simulation experiments. The control results of various controllers are compared and analyzed to verify the effectiveness of the fractional-order sliding mode control method designed in this paper.

Liu, Jingyi, Zhou, Qi, Wang, Jiajia, Lu, Zhaona

Research on Low-Altitude Economic Air Traffic Control Model Based on Spatiotemporal Constraint Reinforcement Learning

2026-99-0580

7/10/2026

With the rapid development of the low-altitude economy—represented by drone logistics, aerial inspections, and air taxis—air traffic has exhibited new characteristics including diverse forms, high density, and significant speed differences. To address these changes, the traditional air traffic control system requires upgrades, particularly in dynamic aircraft scheduling. This study proposes an air traffic control model (DS-ATM) tailored to this domain, built on the Deepseek large model. By integrating spatiotemporal graph neural networks with multi-objective reinforcement learning algorithms, the model achieves real-time path planning and conflict resolution in complex airspace environments. Validated using public datasets such as OpenSky Network, NASA UTM Dataset, and METAR meteorological data, experimental results demonstrate its significant advantages in reducing conflict rates and scheduling delays.

Li, Rui, Zhao, Fangyu, She, Yue, Li, Wujie

Review of Power Management Technology for Turbine Hybrid Electric Propulsion Systems

2026-99-0531

7/10/2026

The turbine hybrid electric propulsion system is an important form of green aviation. Unlike the single form of aviation power scheme, the hybrid energy system is flexible in architecture, uses two or more energy forms, and has diverse energy sources. Under different mission requirements, it needs to meet the requirements of mass balance, energy balance, and power demand, etc. Therefore, The control and distribution management between different energy systems have become the key to hybrid power, and power management technology is one of the key challenges in the development of aviation hybrid power control systems. This paper reviews the current structural forms of aviation turbine hybrid electric propulsion systems, analyzes the current research status of power management technology for aviation hybrid systems, and points out that the online power management method based on optimization is the best power management technology solution for turbine hybrid electric propulsion systems. Establishing a high-precision and realtime on-board power calculation model, breaking through the power management method based on the integrated flight and engine, and improving the applicability of the power management method throughout the service life are important directions for promoting the development of online power management technology.

Cai, Changpeng, Liu, Hao, Gu, Jiangwei, Li, Shunming, Zhang, Haibo

A Methodology for the Conversion from Physics-Based to Ultrafast-Running Data-Driven Powertrain Models for Real-Time Applications

03-19-04-0017

7/3/2026

The virtualization of powertrain systems is a key enabler for modern powertrain development. While physics-based 0D/1D simulation models provide accuracy and interpretability, these models are typically computationally demanding, prolonging the development process and usage throughout the V-cycle. Moreover, achieving real-time-capable simulation models through model simplifications remains challenging, as it often leads to significant losses in accuracy. In contrast, data-driven approaches can achieve high computational efficiency without significantly compromising model accuracy. This opens the possibility for not only online control applications, such as model predictive control or reinforcement learning, but also for computational expensive offline control prototyping using ultrafast-running data-driven digital twins. This work focuses on the elaboration of a scalable methodology for the development of ultrafast-running powertrain models for stationary and transient engine operation. This includes the efficient generation of training data with great variance, data analysis, and preparation, an optimized partitioning method using the Jensen–Shannon distance, feature engineering, model training of a multilayer perceptron (MLP), a long short-term memory (LSTM), and gated recurrent unit (GRU) network, followed by the model evaluation using test data and the concluding model deployment. In order to demonstrate the concept, a calibrated 0D/1D model of a dual-fuel marine main engine provided by WinGD Ltd. for a pure car and truck carrier is utilized as the reference physics-based model. The case study provides a comprehensive examination of the development of ultrafast-running data-driven fuel consumption models in both stationary and transient engine operation. The results show that the proposed methodology yields robust results and minimizes the loss of accuracy to 1.80%–2.14% for the MLP predicting the steady-state fuel consumption and to 0.67%–0.96% (GRU) and 1.52%–1.68% (LSTM) for predicting the transient fuel consumption, while achieving a multiple 104-fold reduction of the real-time factor (RTF) on an identical CPU.

Weller, Louis, Zanelli, Alessandro, Yang, Qirui, Brutsche, Martin, Grill, Michael, Kulzer, André Casal

Trajectory Tracking Control and State Estimation for Highly Automated Vehicles: A System Framework Implemented on U-Shift II

2026-01-0779

7/1/2026

Trajectory tracking control and vehicle state estimation are core functionalities of highly automated vehicles and must operate reliably under strict real-time constraints as well as in the presence of model uncertainties and limited sensor availability. This paper presents an integrated, real-time capable framework for trajectory tracking control and vehicle state estimation, developed within the UShift II research project and implemented on the highly automated vehicle platform. The framework combines nonlinear model predictive control (NMPC) for trajectory tracking with an extended Kalman filter (EKF) for multi-sensor state estimation within a modular system architecture. The NMPC is based on a vehicle model designed for low-speed automated driving maneuvers and explicitly accounts for actuator constraints. Trajectories are tracked based on local planned reference trajectories while ensuring smooth and physically feasible control inputs for underlying control. The EKF fuses measurements from global navigation satellite system (GNSS), inertial sensors, and wheel-speed-based odometry, providing consistent estimates of the vehicle states under varying sensor availability. Particular emphasis is placed on robustness and computational efficiency in order to meet the real-time execution requirements on the target hardware. The complete framework is implemented on automotive-grade real-time hardware and validated on the U-Shift II vehicle platform. Experimental results demonstrate reliable localization performance, smooth and accurate trajectory tracking, and deterministic real-time execution, confirming the suitability of the proposed approach for practical low-speed automated driving applications.

Fuchs, Sören, Neubeck, Jens, Wagner, Andreas

Development and Validation of a One-Dimensional Model for an Opposed-Piston Free-Piston Engine Generator with Parametric Analysis

2026-37-0021

6/9/2026

Opposed-piston free-piston engine generators (OFPEGs) are emerging as a promising technology for next-generation hybrid and electrified transportation systems due to their high efficiency, reduced mechanical complexity, and improved noise, vibration, and harshness (NVH) characteristics. However, due to eliminating the conventional crankshaft mechanism and directly coupling a free-piston engine with linear generators, performance of OFPEG systems is governed by a strong coupling between piston dynamics, in-cylinder combustion processes, and electrical loading conditions. This coupling presents substantial challenges for system design, control, and optimization, limiting the further development and application of OFPEGs. Existing researches lack a comprehensive numerical model that integrates detailed in-cylinder thermodynamic process with control system of linear generator, and quantitative analysis of the effect of piston motion trajectory on system performance remains insufficiently explored. In this study, a novel one-dimensional OFPEG model is developed in Gasdyn and coupled with a linear motor model and a control strategy in MATLAB/Simulink, thus forming a complete numerical model for OFPEG. The model is validated against experimental measurements, demonstrating effective prediction of thermodynamic and dynamic performance with acceptable errors. Based on the validated model, the effects of varying piston motion trajectory on system performance are analyzed. Lower Rt and higher Ωcom and Ωexp are recommended for higher performance. When Rt is reduced to 2.5:1, thermal efficiency and indicated power improve to 36.3% and 3.4 kW, respectively. When Ωcom is increased to 0.6, thermal efficiency and indicated power improve to 35.5% and 3.22 kW, respectively. When Ωexp is increased to 0.6, thermal efficiency and indicated power improve to 36.0% and 3.41 kW, respectively. These improvements are primarily attributed to reduced heat transfer losses and enhanced scavenging efficiency under the modified trajectories. The results provide valuable insights into the optimization of piston motion trajectory to achieve higher performance. Furthermore, the proposed numerical model provides an effective tool for OFPEG design, optimization, and control strategy development, supporting the advancement of high-efficiency, low-carbon OFPEG systems for future transportation applications.

Wang, Jiayu, Morandi, Nicola, Lucchini, Tommaso, FENG, HUIHUA, Jia, Boru, Ren, Peirong

Coordinated Path Tracking and Stability Strategy for Distributed Drive Electric Vehicles Using Model Predictive Control with Dual Feedback Adjustment

10-10-04-0034

6/3/2026

Distributed drive electric vehicles (DDEVs) provide enhanced maneuverability through independent wheel torque control, but coordinating precise path tracking with lateral stability remains challenging under aggressive driving conditions. This paper presents a coordinated control strategy that integrates model predictive control (MPC) for path tracking with a proportional gain controller for stability regulation. The proposed framework adopts a hierarchical design. The path tracking control leverages MPC to compute front steering commands while accounting for vehicle dynamics and preview errors. The stability adjustment uses dual proportional gain controllers to generate an additional yaw moment, which is adaptively balanced through a phase plane coordination mechanism, enhancing yaw stability during path tracking. The generated yaw moment is subsequently distributed to individual in-wheel motors with an optimization torque allocation method, respecting tire force limitations. The effectiveness of the proposed strategy is validated with hardware-in-the-loop (HIL) experiments under a double lane change maneuver. Results show that the coordinated approach improves path following and maintains yaw stability more effectively than conventional methods.

He, Yang, Zhu, Yuzheng, Guo, Ruixin, Zhu, Yueying, Xing, Chao, Liu, Shuangxi, Lin, Yier

Keeping industrial vehicles secure in a digital landscape

26TOFHP06_03

6/1/2026

OEMs, integrators and suppliers must continuously process, assess and identify platform vulnerabilities to prioritize and implement updates that protect systems from cyberattacks and data breaches. Security researchers have demonstrated that the control systems in vehicles and machines are open to attack. In 2010, researchers from the University of Washington and the University of California, San Diego demonstrated that by gaining physical access to a vehicle, they could manipulate critical systems like brakes and engines. Just a few years later, security researchers Charlie Miller and Chris Valasek remotely compromised a vehicle over the internet, controlling steering, braking and acceleration, leading to a 1.4 million vehicle recall. In 2024, researchers at Colorado State University successfully demonstrated a wireless drive-by hack by exploiting vulnerabilities in common electronic logging devices (ELDs). In their proof-of-concept test, they achieved remote control over a truck by reflashing the ELD with malicious firmware, which allowed them to slow down a moving truck and show a design for a truck-to-truck worm virus that could theoretically spread through a fleet.

McGuirk, Finn

Model Reference Adaptive Gain-Scheduled PID control for Robust Heading Stabilization in UAS under Wind Disturbances

2026-26-0723

6/1/2026

Unmanned Aircraft Systems (UAS) are increasingly deployed in diverse missions, and maintaining heading stability in the presence of unpredictable wind disturbance is a significant challenge. This paper proposes a novel model reference adaptive gain-scheduled PID (Proportional-Integral-Derivative) control framework tailored for the heading control of flapping-wing UAS (ornithopter) operating under dynamic wind conditions. The control architecture integrates an estimated wind disturbance value and adaptively tunes the PID gains by minimizing the error between the actual system response and a desired reference model. Gain scheduling mechanism uses airspeed, yaw rate, and estimated wind magnitude to ensure stability. The proposed method is validated on a 6-DOF UAS simulation model subjected to dynamic wind and temperature variation profiles. Comparative results show improved heading accuracy, responsiveness, and robustness over conventional fixed-gain and static gain-scheduled PID controllers, paving the way for safer and more efficient autonomous UAS missions. Also, the approach can be adapted to other platforms in future applications.

M V, Aruna, Melissa, Arul

Electrical Harnessing in Satellite Launch Vehicles of ISRO – Methods for Sustainable, Safe and Reliable Systems

2026-26-0779

6/1/2026

The electrical harness system of satellite launch vehicles functions as the backbone of spacecraft avionics; inter connecting subsystems through complex networks of wires and connectors. An electrical harness is a group of wires bunched together and terminated in connectors. The common insulations used for launch vehicle applications include PTFE, Polyimide, ETFE and TKT. The connectors used are of aerospace grade and connectors tailored for space applications. With over 5000 connectors and 200 km of cables constituting nearly 20% of vehicle mass, the design, fabrication, and sustainability of these systems are critical. The insulations of connectors inserts or the wires are critical for the durability of harness elements. Nevertheless, these insulations are non-expendable and pose disposal challenges and some releases toxic gases when burned or due to vacuum outgassing phenomenon. Also, the cadmium plating which is often used for the environmental resistance of connector shells presents additional risks to the working humans due to its carcinogenic nature and shows tendency to bloom out during storage. This paper presents the methodologies and innovations implemented to develop safe, reliable, and environmentally sustainable harness systems for current and future launch vehicles. Key advancements include the adoption of lean manufacturing practices for waste reduction, the replacement of hazardous cadmium-plated connector shells with stainless-steel alternatives, and the induction of TKT-insulated wires to prevent arc tracking and ensure human-rating compatibility. Additionally, lightweight composite connectors and micro-miniature interconnects are being qualified to support mass optimization in reusable launch vehicles. Through these strategic measures, the study demonstrates how the integration of sustainable materials, safety-oriented design, and process optimization can enhance the performance, safety, and environmental footprint of launch vehicle electrical harness systems.

K S, Nithish, TR, Binny, D S, Praveen Kumar

Hybrid Physics-Informed Neural Network and PID Control for Fault-Tolerant Autonomous Multi-Copters

2026-26-0770

6/1/2026

This paper addresses the critical challenge of fault-tolerant control in autonomous multi-copters, particularly under conditions of one or two rotor failures a scenario that often leads to severe instability and a complete loss of directional control due to unbalanced torque and resultant autorotation. Existing advanced control strategies, including optimal approaches such as LQR, typically require precise system modeling and state estimation, which are difficult to achieve in real-world, dynamic failure scenarios. Alternative methods like fuzzy logic, sliding mode control, and gain-scheduling either lack robust generalization or are impractical for enumerating all possible failure cases. In this work, a hybrid control framework integrating Physics Informed Neural Networks (PINN) with a standard PID controller is proposed for fault-tolerant operation of autonomous multi-copters subject to multiple actuator failures. PINNs incorporate governing physical laws as regularization in their loss functions, allowing them to learn optimal counter-torque actions and thrust balancing necessary to arrest autorotation and stabilize flight, despite limited training data and uncertainty in failure conditions. The calculated moments and thrust commands are executed via a robust PID scheme, enabling reliable real-time implementation and minimizing residual oscillations. This hybrid control architecture demonstrates significant potential to enhance the resilience and operational safety of autonomous multi-copters during unexpected motor failures. By leveraging PINN’s physics-based generalization and PID’s consistent execution, the proposed method offers an adaptive, model-agnostic approach for maintaining stable flight and directional control under severe actuator faults, with implications for next-generation fault-tolerant UAV systems deployed in complex environments.

Charapalle, Samruddhi, Venugopalan, Nandagopalan, Nerkundram Muralidharan, Arun, Sundararaj, Laveen

Electric Health-Monitoring Wiring (E-Wiring) for Aircraft

2026-26-0785

6/1/2026

Modern aircraft depend on extensive electrical wiring networks for power distribution, avionics, and control systems; however, these wiring systems are vulnerable to wear, insulation degradation, and arcing over time, leading to safety risks and costly unscheduled maintenance. This paper introduces an advanced Electric Health-Monitoring Wiring (E-Wiring) system that integrates temperature, current, insulation, vibration, and environmental sensors directly into aircraft wiring harnesses to enable continuous monitoring and intelligent fault detection. Data from these embedded sensors are processed through a distributed edge AI network, forming an Electrical Health Monitoring System (EHMS) capable of real-time diagnostics, predictive maintenance, and fault localization. The architecture comprises smart cable segments with sensor nodes, local harness gateways for edge processing, aircraft-level EHMS integration via AFDX/Ethernet, and cockpit or maintenance displays linked to ground-based cloud analytics for fleet-wide insights. We have an existing method to detect by using acoustic sensing method which can detect ongoing insulation chafing or a cut, they are limited in identifying pre-existing damages and by adding multiple acoustics in the existing wire harnesses it’ll add extra load to the aircraft. To overcome this, the system incorporates Time Domain Reflectometry (TDR) technology to detect both existing and potential wiring faults. The TDR circuitry interfaces with onboard devices, injecting test signals into wiring to pinpoint insulation anomalies or conductor breaks without adding significant weight or complexity. The proposed E-Wiring and EHMS solution enhances aircraft safety, reduces maintenance costs, and improves operational availability, offering a scalable approach for both retrofit and new-generation aircraft.

Tammana, Bala Sai Sri Rohit, Murthy, Harsha, Mendu, HarikaSivaniSunandha

AI Based Energy Sustained Series Hybrid Aircraft

2026-26-0776

6/1/2026

This paper investigates the energy consumption characteristics of series hybrid aircraft with a focus on comparing conventional energy management approaches against an AI-powered optimization framework. The study comprehensively models the energy demands of a series hybrid aircraft across all major flight phases, including Idle & Ground Operations, Taxi, Takeoff, Climb, Cruise, Descent, Approach, Landing, and Rollout & Taxi. For each phase, detailed mathematical formulations are developed to capture power requirements and energy flow, incorporating real-time operational parameters to enhance the accuracy of the energy consumption estimations measured in kilowatt-hours (kWh). The AI-based optimization leverages advanced control strategies, specifically Model Predictive Control (MPC) and Reinforcement Learning (RL) algorithms, to dynamically manage the aircraft’s energy systems. MPC is employed to predict and optimize future energy usage by solving constrained optimization problems over a moving time horizon, ensuring efficient energy distribution while satisfying operational constraints. Concurrently, RL algorithms enable adaptive learning from operational data to improve decision-making in energy management, optimizing performance under varying flight conditions and uncertainties. Comparative analysis demonstrates that the AI-driven series hybrid aircraft achieves significant energy savings compared to conventional methods, quantified in both absolute kWh reductions and percentage improvements. These savings are particularly pronounced during overall phases such as Takeoff, Climb, and Cruise, etc. where optimal control of energy flows directly translates to improved efficiency and extended operational endurance. The findings underscore the potential of AI-integrated control systems in advancing sustainable aviation technologies by enabling smarter, energy-efficient hybrid propulsion. This paper provides a foundation for future development of intelligent energy management systems that can be deployed in next-generation hybrid series aircraft, contributing to reduced environmental impact and enhanced operational performance.

Kanchagar, Amogha

Potential of an In-Cylinder Pressure–Based Combustion Control for Compression Ignition Aviation Engines Operated with Sustainable Aviation Fuels

2026-01-5028

5/29/2026

The aviation industry represents a significant greenhouse gas emitter and aims to reduce net CO2 emissions to zero by 2050. The deployment of sustainable aviation fuel (SAF), alongside measures such as increasing engine efficiency and enhancing ground handling processes, represents a key driver to reach this ambitious goal. SAF exhibits significantly different physical and chemical properties compared to conventional kerosene. The corresponding fuel specification (ASTM D7566 [1]) currently only defines fuel parameters relevant for the use in jet engines. To assess the suitability of SAF for the use in compression ignition (CI) aviation engines, a collaborative project was conducted at TU Wien—Institute of Powertrain and Automotive Technology, together with Austro Engine. ASTM D7566-certified fuels like Hydrotreated Vegetable Oil (HVO), Fischer–Tropsch–Kerosene (FTK), and Alcohol-to-Jet (AtJ) have been investigated on the engine test bench at TU Wien. The core contribution of this study is the experimental evaluation of a real-time capable in-cylinder pressure–based combustion control strategy that enables fuel-flexible and optimized CI engine operation across a wide range of SAF while accounting for mechanical constraints such as peak cylinder pressure and pressure rise rate. To evaluate the potential of such a control system, optimized engine operation was compared to operation with conventional ECU (Engine Control Unit) mapping. Furthermore, the influence of such a real-time combustion process optimization on critical emissions like NOx or soot has been evaluated. Through the implementation of an in-cylinder pressure–based combustion control, a considerable fuel-saving potential could be demonstrated across the entire fuel range. As combustion phasing is optimized toward early crank angle positions, a slight increase in NOx, with a corresponding decrease in soot is observed. Additionally, the use of automotive, piezoresistive pressure sensors was examined regarding a potential serial application. It has been shown that piezoresistive sensors (standard serial parts—calibrated for automotive application) are well-suited for determination of combustion phasing, while in-cylinder peak pressure and its position can only be determined with insufficient accuracy.

Kleissner, Florian, Hofmann, Peter

Energy Saving and Personalized Thermal Comfort Control Based on Reinforcement Learning and Decision Tree

2026-99-1714

5/22/2026

Indoor thermal comfort is closely related to people’s health and work efficiency. Control systems typically consume a large amount of energy to maintain a comfortable thermal environment. Currently, reinforcement learning is widely applied to optimize thermal comfort control systems. However, existing research mainly adopts universal thermal comfort evaluation models that aim to satisfy the majority of people, which makes it difficult to quickly and accurately reflect the specific thermal comfort needs of individuals. As a result, the hot environment is neither comfortable nor energy-efficient in practical use. Therefore, this paper proposes an energy-saving personalized thermal comfort control method based on decision trees and reinforcement learning. First, decision tree learning is used to obtain an individual thermal comfort evaluation model from a small amount of historical data. Then, this individual comfort model is combined with energy consumption to form a reward function, which is used in reinforcement learning to derive personalized thermal comfort control strategies. The experiments show that, compared to traditional methods, this approach can improve user thermal comfort by 43.8% and achieve an energy-saving effect of 30.7%.

Li, Xianying

Adaptive SMPC for Multi-Objective Optimal Scheduling of Offshore Wind Farm Cluster Energy Island System

2026-99-1739

5/22/2026

Based on the multi-objective hierarchical optimization solution method, this paper takes both system balance and scheduling economy into account, and constructs a hierarchical collaborative optimization model for the multi-energy complementary system of offshore energy islands. To address the impact of the volatility and randomness of offshore wind farm clusters on the scheduling of energy island systems, the Stochastic Model Predictive Control (SMPC) method is adopted to optimize and solve the scheduling of offshore energy islands. This paper innovatively proposes a scheduling method based on adaptive variable-step stochastic model predictive control. In the rolling optimization process of SMPC, this method tracks the real-time scheduling deviation degree through the deviation reference coefficient and changes the rolling optimization step size. It solves the problems of insufficient scheduling accuracy and being trapped in local optimization in the rolling optimization process of the traditional stochastic model predictive control scheduling method, and takes both scheduling accuracy and globality into account. The simulation results show that this method can effectively improve the scheduling accuracy and shorten the calculation time.

Huang, Haocheng, Zhang, Jinqi, Zhou, Fengfeng, Yan, Qihui, Xu, Chang, Yin, Gaojun

Toward Human-Centric Autonomous Vehicle Control: A Systematic Model-Based Approach to Motion Sickness Mitigation and Path Tracking

10-10-03-0023

5/22/2026

Autonomous Vehicles (AVs) offer unprecedented opportunities to design control strategies that could be able to simultaneously enhance safety, performance, user experience, time efficiency, and the environmental impact of mobility. However, as automation levels increase, a paradigm shift becomes not only necessary but imperative: the integration of human needs into mobility objectives. This includes not only traditional comfort considerations but also minimizing Motion Sickness (MS), a largely under-explored challenge in control strategy design. In recent literature, several methodologies for modeling and mitigating MS have been proposed, yet their integration into vehicle control logics remains limited, often restricted to isolated and specific case studies, with the research area largely unexplored, particularly with respect to the generalization of the proposed methods. This work introduces a theoretically grounded multi-objective Nonlinear Model Predictive Control (NMPC) framework for coupled vehicle–passenger systems, featuring a novel prediction horizon optimization methodology and adaptive conflict resolution strategies for heterogeneous performance metrics to mitigate motion-induced discomfort while ensuring accurate path tracking. Human-centric control design is pursued by embedding increasingly complex vehicle models and MS metrics, further addressing the trade-off between model fidelity and computational feasibility, and introducing a methodological standpoint for selecting the optimal prediction horizon in the presence of heterogeneous and conflicting control objectives, an aspect often overlooked in current literature. An experimental campaign supports model calibration and validation, while multi-scenario simulations demonstrate the framework’s ability to balance tracking performance, computational efficiency, and passenger comfort.

Ponticelli, Lorenzo, Bottiglione, Francesco, Rini, Gabriele, Timpone, Francesco, Sakhnevych, Aleksandr

Wavelet-Based Spatio-Temporal Fusion Network for Electromyographic Decoding in Bionic Hand Control Systems

2026-99-0744

5/15/2026

Surface electromyography (EMG) signals are essential for facilitating intuitive interactions between humans and bionic hands. However, their inherent non-stationarity, low signal-to-noise ratio, and significant inter-individual variability present considerable obstacles to precise decoding. To overcome these challenges, this study proposes a novel recognition framework combining wavelet packet decomposition and a dynamic graph convolutional-Transformer model. The process starts with multi-layer wavelet packet decomposition and adaptive threshold denoising, effectively removing noise while retaining critical signal features. Subsequently, a dynamic graph convolutional network is employed to capture spatial interactions among multi-channel electrodes, and a Transformer encoder models long-term temporal dependencies within the signals. By integrating these methods, the model generates a fused feature representation that incorporates both spatial and temporal correlations. Experimental results demonstrate that the proposed model provides enhanced robustness to noise and achieves greater classification accuracy compared to conventional methods.

Huang, Rui, Zhao, Yue, Yang, Penghua, Zhu, Jintao, Xiong, Xibei

Multi-Mode Control Strategy for Controllable Vehicle Suspension Systems

2026-99-0712

5/15/2026

The suspension system with variable damping and variable stiffness actuators can realize four-quadrant mechanical output, effectively combining the energy efficiency of the semi-active suspension with the performance levels approaching those of active suspensions. However, the practical effectiveness of this system depends heavily on the ability of the control strategy to adapt to different driving conditions. In order to meet this challenge, this research has developed a multi-mode suspension collaborative control strategy to optimize energy efficiency and ride comfort in various operating scenarios. Based on the four-quadrant characteristics of the actuator, a suspension mode switching framework has been established, and the suspension work is divided into passive, semi-active, pseudo-active and active modes. In order to determine the appropriate switching boundary, first calculate the root mean square (RMS) value of the sprung mass acceleration and suspension dynamic deflection under passive conditions. With the existing human comfort sensitivity as a reference, the switching threshold of sprung mass acceleration is 0.527 m/s2, and the switching threshold of suspension dynamic deflection is 8.31×10−3m, and the corresponding conversion rules are formulated. Then, the LQR controller optimized by the genetic algorithm is used to allocate the control force adaptively according to the suspension mode to realize cooperative multi-mode operation. The simulation results on B-D composite road surfaces show that compared with traditional passive suspension, this method can reduce the sprung mass acceleration, suspension dynamic deflection and tire dynamic load by 10.59%, 16.65% and 32.9% respectively. These results confirm that the collaborative control strategy significantly improves the ride comfort, vehicle adaptability and overall performance in complex road conditions.

Li, Zhiying, Li, Jei, Zhu, Anding, Bai, Xianxu, Li, Weihan, Li, Rui

Torque Coordination Control Strategy for Dual-Motor Electric Vehicles Considering Load Transfer and Slip Energy Dissipation

2026-99-0709

5/15/2026

To address the issues of significant slip energy dissipation induced by severe tire slip, degradation of vehicle control stability, and insufficient accuracy of vehicle speed tracking under low-adhesion road conditions, a torque coordination control strategy for dual-motor electric vehicles (DM-EVs) considering load transfer and slip energy dissipation is proposed. First, a vehicle dynamics model integrating suspension system dynamics and tire slip characteristics is developed, fully accounting for the influence of front-rear axle load transfer on the tire slip ratio. Next, founded on the energy dissipation mechanism of tire slip, a quantitative model for energy dissipation during tire slip is developed. Finally, a longitudinal coordinated control system for vehicles according to nonlinear model predictive control (NMPC) is introduced. By comprehensively considering the tire slip ratio and vehicle load distribution, multi-objective coordinated optimization of wheel torque is achieved. Simulation results under constant acceleration conditions on low-adhesion roads indicate that significant slip phenomena occurred in the wheels of both the without slip ratio controller and the PID controller, failing to achieve stable vehicle control. Simulation results in virtual traffic scenarios reveal that, compared to the other two controllers, the proposed controller exhibits significant reductions in key performance metrics: the RMS value of total tire slip ratio is reduced by 84.95% and 87.34%, total tire slip energy dissipation is reduced by 94.95% and 96.53%, and total tire wear volume is reduced by 93.78% and 95.71%, respectively. These results demonstrate the performance of the introduced control strategy.

Hou, Yingming, Li, Jie, Bai, Xianxu

Coordinated Stability Control for Active Rear Steering Vehicles Based on Dynamic Stability Region

2026-99-0713

5/15/2026

To improve the handling stability of four-wheel steering/drive vehicles under complex high-speed maneuvers, this study proposes a coordinated control strategy that incorporates Active Rear Steering (ARS) and Direct Yaw Moment Control (DYC) based on a dynamic stability region. Firstly, a four-wheel steering vehicle dynamics model including lateral motion and yaw motion is established, and the ideal values of the control variables are determined. Secondly, combined with the fuzzy control theory and double-line method, the boundary of the dynamic stability region is obtained in the sideslip angle-sideslip angle rate β−β̇ phase plane, and the vehicle state is categorized into stable, unstable, and critical stable region. Then, A hierarchical control architecture is designed based on the stability boundary. The upper controller comprehensively solves the target rear wheel angle and additional yaw moment through feedforward feedback control; the coordinated control layer allocates control weights according to the stable state of the vehicle; the lower controller optimizes torque distribution through quadratic programming. Finally, the control strategy is validated by MATLAB/Simulink and CarSim co-simulation platform. The results show that the proposed control strategy reduces the RMS values of yaw rate and sideslip angle by 23.1% and 28.5% respectively, significantly improving the handling stability of the vehicle.

Nie, Kehe, Chen, Jin, Wang, Falong, Li, Ren, Bai, Xianxu

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