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

  • Special Issue on Computational Intelligence-based Control and Estimation in Mechatronic Systems
  • Published:
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Abstract

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.

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Funding

Funding

Funding was provided by National Natural Science Foundation of China (CN) (62003305) and Natural Science Foundation of Zhejiang Province (Y21F010051).

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Authors and Affiliations

  1. College of Information Engineering, Zhejiang University of Technology, Hangzhou, China

    Zhe Sun, Jiayang Zou, Defeng He & Wei Zhu

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  1. Zhe Sun
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  2. Jiayang Zou
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  3. Defeng He
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  4. Wei Zhu
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Correspondence to Zhe Sun.

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Sun, Z., Zou, J., He, D. et al. Path-tracking control for autonomous vehicles using double-hidden-layer output feedback neural network fast nonsingular terminal sliding mode. Neural Comput & Applic 34, 5135–5150 (2022). https://doi.org/10.1007/s00521-021-06101-8

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  • DOI: https://doi.org/10.1007/s00521-021-06101-8

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