Browse Topic: Control systems
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.
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.
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.
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.
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.
Robot Arm Tracking Control refers to the control of robot end effectors following a prescribed trajectory as their movement in robotic systems. The work presents a combination of Kalman Filter Based Dynamic System Tracking with Reinforcement Learning Based Trajectory Planning. These two aspects of tracking and planning help the robotic manipulator dynamically track a target that is located on an arbitrary moving path. In particular, by using Kalman filtering to estimate the position of a moving target and to compensate for sensor noise and sparse sampling, we take high-precision estimation values of each point’s coordinates along the target trajectory as a reliable basis to build a policy network using reinforcement learning. Based on it, the robot manipulator could produce effective motion planning under its own dynamic capabilities and physical constraint limit. Comprehensive simulation results illustrate advantages of the new algorithm against the classical control method, confirm that the novel technique achieves better performance both in accuracy and computation efficiency. Also, this mixed control system can deal with complex moving path for track target object. Even when meet different obstacle and not sure measurement, it still works well with other moving obstacle in many conditions. This can be strong to face other dynamic obstacle even if have different situation with changing obstacle and uncertain data. It shows that this paper works as an attempt toward optimal solution to combine the model-based technique together with data-driven approach aiming to support real-time, highly accurate, adaptive prediction is based control technique, promising applications into industry and promoting more improved works related.
The aging of the population has been a key issue worldwide, with mobility and fall of the elderly an important problem to be solved. In this paper, we propose an elderly mobility assist system based on the intelligent power-assisted device consisting of an assistive cane and an intelligent companion. It has the functions of standing support after falling, daily support and on-site rest. The assistive cane adopts a two-stage expansion mechanism of crank and slider structure, which forms a stable triangular support after unfolding, so that the patient can stand safely. The intelligent companion platform is driven by drive wheels, equipped with pushrod motors and vacuum suction devices, it can automatically approach the user and form an stable support column when the cane is in the out-of reach range; the control system is designed by combining microcontroller, camera object recognition, wristband remote control, to realize automatic steering and autonomous navigation at differential speed. The overall design satisfies the requirements of safety and strength through mechanical verification and stress analysis. The proposed system can help the elderly people to recover from falls better and enhance their independence and safety in their daily walks.
Atmospheric turbulence is a major source of uncertainty for unmanned rotorcraft operating in confined or disturbed environments, where robust trajectory planning requires reliable bounds on vehicle response. High-fidelity turbulence models are typically too computationally demanding for onboard use and difficult to integrate into planning frameworks. This paper presents a Control Equivalent Turbulence Input (CETI)–based approach to characterize turbulence effects on the inner-loop dynamics of a small unmanned helicopter and to derive disturbance-induced state deviation bounds suitable for robust planning. CETI models are identified from manually piloted hover flight tests of the unmanned research helicopter midiARTIS using a linear bare-airframe model and a Kalman filter for disturbance estimation. CETI transfer functions are fitted to averaged power spectral densities of the extracted disturbance inputs. The resulting model is validated by reproducing the identified transfer functions and by comparing open-loop simulation results to flight-test data in both time and frequency domain. Based on simulations with CETI inputs, probabilistic bounds on state deviations are derived and related to measured flight-test responses. The results demonstrate that the proposed CETI workflow provides a compact and computationally efficient turbulence surrogate that captures the dominant effects of atmospheric gusts on rotorcraft dynamics and is well suited for inner-loop performance assessment and as an input to robust model predictive control algorithms.
The Enhanced Tiltrotor blade, also known as the RGF3 blade, represents a major milestone in Leonardo Helicopters Division's pursuit of advanced rotorcraft technology. Developed at the Yeovil facility in the United Kingdom as part of a dedicated program and in collaboration with the European Clean Sky 2 initiative, it is a key enabler for the Next Generation Civil Tiltrotor Technology Demonstrator. Leveraging the AW609 airframe, the NGCTR integrates a new lateral rotor control system and a V-tail with ruddervators to expand maneuverability and control authority. The RGF3 blade combines aerodynamic efficiency with manufacturability, cost effectiveness, and certification readiness. Innovations include advanced airfoil families, highly swept anhedral tips, dual-redundant anti-ice systems, and full compatibility with legacy components. A comprehensive test campaign—covering structural loads, lightning and bird strikes, icing, and wind tunnel validation—confirmed its robustness and performance. The RGF3 blade embodies Leonardo's vision for high-speed, sustainable, and reliable next-generation rotorcraft.
Full state feedback offers theoretically guaranteed multi-axis stability, making it superior to conventional PID controllers. There is however one drawback, a full state controller has a mathematical difficulty if the B matrix is not square and thus not invertible. This is the case for helicopters with 6 degrees of freedom and 4 inceptors. Variations of linear quadratic regulators are a work around, however complexity dramatically increases. Best would be a direct solution to the original problem. This is the breakthrough result of this paper. This paper documents an approach which removes the analysis roadblock by partitioning the 6 x 6 system "A" matrix into two groups of 4 x 4 matrices. The 4x4 matrices are individually stabilized with full state gain matrices. One matrix is designated “Driver Matrix” which provides actuator commands. The other matrix is designated "Reference Matrix" which provides references. The two matrices are coupled together by requiring that the driver matrix follow references generated by the reference matrix. With each matrix individually stabilized, the coupled combination is also stabilized. Computation of flight dynamics states (u, v, w, p, q, r) is shared between the matrices. Initial results are very encouraging, showing an originally sluggish, heavy lift helicopter having now concise decoupled responses to pitch and roll commands. Stability derivatives are recomputed during flight allowing coverage over the whole flight envelope. A handling qualities task has been defined to relocate a 40 ft standard seaborne container directed by a pilot in a ground control station. Cooper Harper ratings of this task have demonstrated favorable Level 1 handling qualities if use is made of an automated lateral repositioning command.
This organizational process survey provides insight into the technical aspects of approved airworthy aircraft modifications applied in government organization vertical lift flight test. The publication reviews processes applied by the National Research Council of Canada's Flight Research Laboratory (NRC-FRL) and its Airworthiness Control System to enable research flight testing. Dominated by the need for integrating experimental payloads, the NRC-FRL embeds a Design and Fabrication Service organization for modification of internal and external client projects and flight test aircraft. In context of experimental flight testing, this work reviews technical information on process, facilities, and methodology for airworthy integration of flight test payloads. Information is used to synthesize recommendations in experimental vertical lift flight testing that satisfy both formal (regulated compliance) and informal (compliance intent) airworthiness requirements.
This paper presents the development, optimization, and flight test validation of a Trajectory Control System (TCS)-based flight control system for a tiltwing unmanned aerial vehicle. The TCS is a configuration-independent middle-loop longitudinal controller for vertical takeoff and landing aircraft and is integrated here with explicit model following inner-loop controllers, inverse propulsor models, and a tiltwing-specific control allocation scheme. The resulting flight control system provides coordinated control across vertical flight mode, hybrid flight mode, transition flight mode, and forward flight mode while relying on a concise feedback set and requiring only airspeed from the air data system. The control laws are obtained using a formal constrained optimization framework and transferred directly from simulation to flight without additional on-site retuning. Flight test results from piloted, semi-autonomous, and fully autonomous operations demonstrate stable and predictable behavior throughout the flight envelope, including tight hover performance, simultaneous climb rate and speed tracking in hybrid flight, and successful departure and arrival transitions at multiple speeds. Selected simulation-versus-flight comparisons further show that the nonlinear model captures the dominant trends in the measured response while also identifying specific aerodynamic and transition regime effects that warrant further refinement. Overall, the results demonstrate that the TCS + EMF architecture provides a practical and effective control solution for tiltwing VTOL aircraft.
This work describes the flight control system architecture of the VSDDL VT-03-s Shadow, a cost-effective subscale aircraft used as a testbed for novel flight control schemes. The highlight is the Maneuver Control System comprising the Trajectory Control System, which facilitates Simplified Vehicle Operations, and the Tactical Maneuvering System, which permits more aggressive maneuvering. The control laws permit the selection of both vertical takeoff and landing and conventional takeoff and landing modes of operation. Flight test results shown include transitions between vertical and forward flight modes performed using both Trajectory Control System and Tactical Maneuvering System, limited aerobatic maneuvering performed using the Tactical Maneuvering System, and demonstration of some of the automatic flight functions and capabilities.
This paper presents an adaptive model predictive control (MPC) framework for nonlinear urban air mobility (UAM) vehicles operating across the full flight envelope. The proposed approach leverages a linear parameter-varying (LPV) representation to update the predictive model online, enabling accurate capture of strongly nonlinear and time-varying dynamics associated with distributed electric propulsion (DEP) eVTOL aircraft. To systematically address the highdimensional and coupled nature of MPC tuning, a multi-objective evolutionary optimization strategy based on NSGAII is employed, incorporating proper normalization of states and control inputs to ensure balanced weighting and meaningful exploration of the design space. The resulting controller explicitly accounts for actuator constraints and enables reconfigurable control allocation for fault-tolerant operation. The framework is evaluated in nonlinear simulations using NASA's Generic Urban Air Mobility (GUAM) model and benchmarked against a robust servomechanism linear quadratic regulator (RSLQR). Results demonstrate that the proposed adaptive MPC achieves improved trajectory tracking and enhanced robustness under both nominal conditions and actuator degradation scenarios, including partial motor failure, while maintaining constraint satisfaction throughout all flight regimes.
This paper presents the design and simulation-based evaluation of a configuration-independent Trajectory Control System (TCS) for multiple vertical takeoff and landing (VTOL) vehicles. The TCS provides a unified, middle-loop longitudinal control system applicable to lift-plus-cruise, tiltwing, and vectored-thrust configurations. Developed under the Simplified Vehicle Operations (SVO) paradigm, the TCS computes thrust-to-weight commands from normalized vertical and horizontal acceleration using inertial frame force-balance relationships and allocates the resulting trajectory requirements across the available propulsors. The governing TCS equations, propulsor-share framework, and mode structure remain common across configurations, while configuration-specific effects enter only through mode thresholds, inverse propulsor models, and control allocation. The control laws require only attitude, angular rate, fore-aft acceleration, and vertical velocity feedback. Subscale simulation comparisons across three dissimilar VTOL vehicles demonstrate closely grouped longitudinal response characteristics together with broadly comparable departure and arrival transition behavior, supporting the predicted configuration-independent formulation and its suitability for pilot-intuitive operation. These results establish a scalable longitudinal control approach for next-generation VTOL vehicles. The simulation-based findings are further supported by the broader flight test progression of the three configurations reported in prior work.
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