Regular Papers

International Journal of Control, Automation and Systems 2021; 19(1): 76-87

Published online October 21, 2020

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

© The International Journal of Control, Automation, and Systems

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

Zengke Jin, Zhenying Liang*, Xi Wang, and Mingwen Zheng

Shandong University of Technology

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.

Keywords Input delay, RBF Neural Network, sliding mode, tracking control, trailers.

Article

Regular Papers

International Journal of Control, Automation and Systems 2021; 19(1): 76-87

Published online January 1, 2021 https://doi.org/10.1007/s12555-019-0796-8

Copyright © The International Journal of Control, Automation, and Systems.

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

Zengke Jin, Zhenying Liang*, Xi Wang, and Mingwen Zheng

Shandong University of Technology

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.

Keywords: Input delay, RBF Neural Network, sliding mode, tracking control, trailers.

IJCAS
July 2024

Vol. 22, No. 7, pp. 2055~2340

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