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Adaptive Backstepping Sliding Mode Control of Tractor-trailer System with Input Delay Based on RBF Neural Network

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Abstract

In this paper, an adaptive sliding mode neural network(NN) control method is investigated for input delay tractor-trailer system with two degrees of freedom. An uncertain camera-object kinematic tracking error model of a tractor car with n trailers with input delay is proposed. Radial basis function neural networks(RBFNNs) are applied to approximate the unknown functions in the error model. A sliding mode surface with variable structure control is designed by using backstepping method. Then, an adaptive NN sliding mode control method is thus obtained by combining Lyapunov-Krasovskii functionals. The controller realizes the global asymptotic trajectories tracking of the kinematics system. The stability of the closed-loop system is strictly proved by the Lyapunov theory. Matlab simulation results demonstrate the feasibility of the proposed method.

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Authors and Affiliations

  1. School of Mathematics and Statistics, Shandong University of Technology, Zibo, China

    Zengke Jin, Zhenying Liang, Xi Wang & Mingwen Zheng

Authors
  1. Zengke Jin
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  2. Zhenying Liang
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  3. Xi Wang
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  4. Mingwen Zheng
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Corresponding author

Correspondence to Zhenying Liang.

Additional information

Recommended by Associate Editor Quoc Chi Nguyen under the direction of Editor Myo Taeg Lim.

This work was supported by the National Natural Science Foundation of China (61473179, 61903234), Shandong Procincial Natural Science Foundation (ZR2017LF011, ZR2019MF008)

Zengke Jin received his B.S. degree from the School of Mathematics, Inner Mongolia University for Nationalities in 2017. He is currently an M.S. student at the School of Mathematicsand Statistics, Shandong Universityof Technology. His research interests include nonlinear control, visual servoing feedback control, and neural network control.

Zhenying Liang received her Ph.D. degree from the Department of Control Science and Engineering, University of Shanghai for Science and Technology in 2011. She received her B.S. and M.S. degrees in mathematics from Shandong Normal University in 1986, and Liaoning Normal University in 1991, respectively. Her research interests cover nonlinear control, robust control, and visual servoing feedback control.

Xi Wang received her B.S. degree in School of Mathematics from Changzhi University, ChangZhi, China in 2018, and studying in the School of Mathematics and Statistics from Shan Dong University of Technology.

Mingwen Zheng received his Ph.D. degree from the Beijing University of Postsand Telecommunications in 2018. He received his B.S. degree from the School of Science, Shandong University of Technology in 2002, and an M.S. degree from School of Computer and Communication Engineering, China University of Petroleum in 2009. His current research interests include complex dynamical network, neural network, and memristors.

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Jin, Z., Liang, Z., Wang, X. et al. Adaptive Backstepping Sliding Mode Control of Tractor-trailer System with Input Delay Based on RBF Neural Network. Int. J. Control Autom. Syst. 19, 76–87 (2021). https://doi.org/10.1007/s12555-019-0796-8

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  • DOI: https://doi.org/10.1007/s12555-019-0796-8

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