A Model-Free Control Strategy for Vehicle Lateral Stability With Adaptive Dynamic Programming

This article presents a nonmodel-based controller design for vehicle dynamic systems to improve lateral stability, where output tracking control and adaptive dynamic programming approaches are employed to track the desired yaw rate and, at the same time, mitigate the sideslip angle, roll angle, and...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2020-12, Vol.67 (12), p.10693-10701
Main Authors: Sun, Weichao, Wang, Xin, Zhang, Changzhu
Format: Article
Language:English
Subjects:
Adaptation models
Adaptive control
Adaptive dynamic programming (ADP)
Asymptotic stability
Computer simulation
Control methods
Control stability
Control systems design
Controllers
Dynamic programming
Dynamic stability
Iterative methods
Lateral stability
Learning
model-free control
Optimization
Rolling motion
Sideslip
Signal processing
Stability criteria
Tire force
Tires
Tracking control
Vehicle dynamics
vehicle lateral stability
Wheels
Yaw
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Summary:This article presents a nonmodel-based controller design for vehicle dynamic systems to improve lateral stability, where output tracking control and adaptive dynamic programming approaches are employed to track the desired yaw rate and, at the same time, mitigate the sideslip angle, roll angle, and roll rate of the vehicle. Moreover, different from some existing optimization methods in control allocation, the proposed control strategies, which distribute tire forces by learning, are only using the information of states, input, and reference signal instead of the knowledge of the vehicle system. The iterative process repeatedly uses the information about state and input to calculate the feedback gain. It can significantly reduce the learning time and computational burden. The effectiveness of the proposed controller design method is shown by CarSim simulations.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2019.2958308