Browse Topic: Optimization
With the rapid advancement of Unmanned Aerial Vehicle (UAV) technology, their assigned missions have become significantly more intricate. Individual UAVs are no longer sufficient to meet these diverse and demanding requirements. There is now a shift towards employing multiple UAVs operating collaboratively to address complex tasks, replacing the reliance on singular units. This study focuses on the complexities of coordinated flight within UAV formations. A dynamic consensus optimal control algorithm is proposed for distributed formations, grounded in optimal control theory. Furthermore, the enhanced control method is validated via simulation on a semi-physical visualization platform, effectively closing the gap between real-world formation requirements and simulation outcomes. The results from these simulations underscore that the proposed method effectively preserves UAV formation integrity and demonstrates exceptional applicability in real-world scenarios
ABSTRACT Today’s combat vehicle designs are largely constrained by traditional manufacturing processes, such as machining, welding, casting, and forging. Recent advancements in 3D-Printing technology offer tremendous potential to provide economical, optimized components by eliminating fundamental process limitations. The ability to re-design suitable components for 3D-printing has potential to significantly reduce cost, weight, and lead-time in a variety of Defense & Aerospace applications. 3D-printing will not completely replace traditional processes, but instead represents a new tool in our toolbox - from both a design and a manufacturing standpoint
ABSTRACT Modern electronic control units (ECUs) typically contain many physically based models represented by a complex structure of maps, curves and scalar parameters. The purpose of these models is to monitor or predict engine values that are normally measured by actual sensors. If the model structure is a good representation of the physical system and the parameters are well fitted, such a model can replace the sensor and serve as a virtual sensor to reduce the cost and complexity of the overall system. Virtual sensors are commonly used in the ECU for predicting engine torque, air pressure and flow, emissions, catalyst temperature, and exhaust gas temperatures. To ensure an optimal prediction quality of these models, their parameters need to be calibrated using real measurement data collected, e.g., in the vehicle or in the test cell. Due to the models’ complexity and the high number of parameters, a manual calibration is very time consuming or even impossible. Instead, iterative
ABSTRACT The study describes the development of a plug-in module of the realistic 3D Digital Human Modeling (DHM) tool RAMSIS that is used to optimize product development of military vehicle systems. The use of DHM in product development has been established for years. DHM for the development of military vehicles requires not only the representation of the vehicle occupants, but also the representation of equipment and simulation of the impact of such equipment on the Warfighter. To simulate occupants in military vehicles, whether land or air based, realistically, equipment must become an integral part of the extended human model. Simply attaching CAD-geometry to one manikin’s element is not sufficient. Equipment size needs to be scalable with respect to anthropometry, impact on joint mobility needs to be considered with respect to anatomy. Those aspects must be integrated in posture prediction algorithms to generate objective, reliable and reproducible results to help design engineers
ABSTRACT The IGVC offers a design experience that is at the very cutting edge of engineering education, with a particular focus in developing engineering control/sensor integration experience for the college student participants. A main challenge area for teams is the proper processing of all the vehicle sensor feeds, optimal integration of the sensor feeds into a world map and the vehicle leveraging that world map to plot a safe course using robust control algorithms. This has been an ongoing challenge throughout the 26 year history of the competition and is a challenge shared with the growing autonomous vehicle industry. High consistency, reliability and redundancy of sensor feeds, accurate sensor fusion and fault-tolerant vehicle controls are critical, as even small misinterpretations can cause catastrophic results, as evidenced by the recent serious vehicle crashes experienced by self-driving companies including Tesla and Uber Optimal control techniques & sensor selection
ABSTRACT Model Based Systems Engineering (MBSE) has been a dominant methodology for defining and developing complex systems; however, it has not yet been paired with cutting-edge digital engineering transformation. MBSE is constrained to represent a whole system, but lacks other capabilities, such as dynamic simulation and optimization, as well as integration of hardware and software functions. This paper provides the key elements for developing a Smart MBSE (SMBSE) modeling approach that integrates Systems Engineering (SE) functionality with the full suite of other development tools utilized to create today’s complex products. SMBSE connects hardware and software with a set of customer needs, design requirements, program targets, simulations and optimization functionalities. The SMBSE modeling approach is still under development, with significant challenges for building bridges between conventional Systems Engineering methodology, with additional capabilities to reuse, automate
ABSTRACT For this particular effort, the U.S. Army Tank Automotive Research Development and Engineering Center (TARDEC) Center for Systems Integration (CSI) was tasked to develop a buoyancy/survivability kit that would serve multiple functions. The underbody kit would meet or surpass current required protection levels. Plus the kit was to ensure that the LAV-25A2 (Light Armored Vehicle) continues to meet the swim requirement. However, the overarching objective is to meet the survivability, ground mobility, and water mobility requirements. Combining the accomplishments in the TARDEC & PM-LAV (Program Manager for the Light Armored Vehicle) survivability program in 2013-2014 with the TARDEC & PM-LAV buoyancy/survivability kit developed in 2015-2016, the overall weight is decreased, water mobility is improved, and survivability is significantly improved. This is a unique challenge as a combination of buoyancy, mine blast, and structural requirement on a ground military vehicle is novel
ABSTRACT A discussion on the utility of physics-based compact thermal models to guide the design, integration, operation and control of thermally sensitive vehicle components is presented. Effective component selection requires honest and accurate representation of the key performance attributes expressed by physics-based models. Parallel developments and lessons learned from the Electronics Industry on component packaging and characterization is discussed. An example application of a physics-based model driven design is presented for an Electrical Energy Dissipater design used on typical hybrid vehicles. Low fidelity models are used early in the design to support system requirements decomposition into discreet design attributes. High fidelity thermal and electromagnetic models are used to explore the design space and to optimize performance metrics. Accurate and robust reduced order thermal models are used for the continuous prognostic, diagnostic monitoring and control of the device
ABSTRACT Parametric analysis is an essential step in optimizing the performance of any system. In robotic systems, however, its usability is often limited by the lack of complex yet repeatable experiments required to gather meaningful data. We propose using the Robotics Interactive Visualization and Experimentation Toolbox (RIVET) in order to perform parametric analysis of robotic systems
ABSTRACT Although bio-inspired legged robots have advantageous mobility, they can be very inefficient. Their intrinsic walking mobility is sometimes outweighed by the inefficiency of their drive-train. Some of these inefficiencies are due to collision losses, but they are also due to suboptimal powering schemes. This paper addresses the powering schemes and seeks to clearly delineate an optimal solution to powering the walking motion of a two-legged or biped walker. We examine a simplified model of locomotion called the “rocket car” to extract the meaningful parameters that affect time and energy cost. Using Pontryagin’s Maximum Principle, we dissect the cost function, the state equation, co-state equation, and control input constraints to describe the optimal control. The result of the paper shows a “bang-off” control, and we describe the “coasting line” between these extremes. It is not possible to find a complete closed-form solution for the problem, and numerical methods, such as
ABSTRACT The IGVC offers a design experience that is at the very cutting edge of engineering education, with a particular focus in developing engineering control/sensor integration experience for the college student participants. A main challenge area for teams is the proper processing of all the vehicle sensor feeds, optimal integration of the sensor feeds into a world map and the vehicle leveraging that world map to plot a safe course using robust control algorithms. This has been an ongoing challenge throughout the 27 year history of the competition and is a challenge shared with the growing autonomous vehicle industry. High consistency, reliability and redundancy of sensor feeds, accurate sensor fusion and fault-tolerant vehicle controls are critical, as even small misinterpretations can cause catastrophic results, as evidenced by the recent serious vehicle crashes experienced by self-driving companies including Tesla and Uber Optimal control techniques & sensor selection
ABSTRACT This paper focuses on the application of a novel Additive Molding™ process in the design optimization of a combat vehicle driver’s seat structure. Additive Molding™ is a novel manufacturing process that combines three-dimensional design flexibility of additive manufacturing with a high-volume production rate compression molding process. By combining the lightweighting benefits of topology optimization with the high strength and stiffness of tailored continuous carbon fiber reinforcements, the result is an optimized structure that is lighter than both topology-optimized metal additive manufacturing and traditional composites manufacturing. In this work, a combat vehicle driver’s seatback structure was optimized to evaluate the weight savings when converting the design from a baseline aluminum seat structure to a carbon fiber / polycarbonate structure. The design was optimized to account for mobility loads and a 95-percentile male soldier, and the result was a reduction in
ABSTRACT Autonomous vehicles rely on path planning to guide them towards their destination. These paths are susceptible to interruption by impassable hazards detected at the local scale via on-board sensors, and malicious disruption. We define robustness as an additional parameter which can be incorporated into multi-objective optimization functions for path planning. The robustness at any point is the output of a function of the isochrone map at that point for a set travel time. The function calculates the sum of the difference in area between the isochrone map and the isochrone map with an impassable semi-circle hazard inserted in each of the four cardinal directions. We calculate and compare two different Pareto paths which use robustness as an input parameter with different weights. Citation: T. Jonsson Damgaard, M. Rittri, P. Franz, A. Halota “Robust Path Planning in the Battlefield,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA
ABSTRACT This paper presents a modeling and simulation framework for tracked vehicles for ride comfort and load prediction analysis. The development began with the identification of the key issues such as formulations, integration schemes and contact (with friction) modeling on which the comparative studies are conducted. Based on the results of the investigations, the framework and process for the modeling and simulation of tracked vehicles are established and appropriate algorithms for contact and friction are developed. To facilitate the modeling and simulation process, a Python-based modeling environment was developed for process automation, design optimization and design of experiment. The developed framework has been successfully applied to the dynamic load predication of a M1A1 based Joint Assault Bridge (JAB). The parameter optimization enabled with the Python-based process automation tool helps improve the design and modification of vehicles for significantly improved fatigue
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