Path-tracking control for autonomous vehicles using double-hidden-layer output feedback neural network fast nonsingular terminal sliding mode

In this paper, a double-hidden-layer output feedback neural network fast nonsingular terminal sliding mode control strategy is developed for path-tracking tasks of autonomous vehicles. First, a vehicle kinematic-and-dynamic model is established to describe the vehicle’s fundamental lateral dynamics...

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Bibliographic Details
Published inNeural computing & applications Vol. 34; no. 7; pp. 5135 - 5150
Main Authors Sun, Zhe, Zou, Jiayang, He, Defeng, Zhu, Wei
Format Journal Article
LanguageEnglish
Published London Springer London 01.04.2022
Springer Nature B.V
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Summary:In this paper, a double-hidden-layer output feedback neural network fast nonsingular terminal sliding mode control strategy is developed for path-tracking tasks of autonomous vehicles. First, a vehicle kinematic-and-dynamic model is established to describe the vehicle’s fundamental lateral dynamics in path-tracking behavior. Afterwards, detailed design procedure of the proposed controller is shown, where the control system’s stability is verified in the Lyapunov sense. Finally, MATLAB-Carsim co-simulations are executed for the aim of testing the control performance. Simulation results illustrate that the designed control algorithm possesses remarkable superiority reflected in higher tracking precision, faster convergence rate and firmer robustness in comparison with a conventional sliding mode controller and a nonsingular terminal sliding mode controller.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-021-06101-8