Path tracking of unmanned surface vehicle based on improved adaptive sliding mode control algorithm

Mengge Liu; Linghai Kong; Chen Cheng; Yongzheng Li

doi:10.1117/12.3010699

1 December 2023 Path tracking of unmanned surface vehicle based on improved adaptive sliding mode control algorithm

Mengge Liu, Linghai Kong, Chen Cheng, Yongzheng Li

Proceedings Volume 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023); 129400F (2023) https://doi.org/10.1117/12.3010699
Event: Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 2023, Sipsongpanna, China

Abstract

Aiming at the path tracking problem of unmanned surface vehicle, a sliding mode control algorithm enhanced with adaptive control technology is proposed. Adaptive control technology is used to predict the boundary value of unknown external environment interference. In order to improve the robustness of the system and the convergence rate of path tracking, the optimization algorithm is designed based on the hyperbolic tangent function control reaching law. A new double power combination function is proposed as the control law to design the sliding mode control algorithm to control the forward and steering of unmanned surface vehicle. The chattering phenomenon caused by sliding mode control is solved effectively and the convergence speed of path tracking is improved. The curve fitting method is utilized to realize the effective tracking of any planned flight path. The simulation results demonstrate that the proposed adaptive sliding mode control algorithm is able to ensure unmanned surface vehicle track the upper reference path accurately under the time-varying disturbance of wind, waves and currents. In additional, the adaptive sliding mode control algorithm embedded an approach control law, called new double power function, is confirmed that has strong robustness and fast convergence rate of path tracking.

Citation Download Citation

Mengge Liu, Linghai Kong, Chen Cheng, and Yongzheng Li "Path tracking of unmanned surface vehicle based on improved adaptive sliding mode control algorithm", Proc. SPIE 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 129400F (1 December 2023); https://doi.org/10.1117/12.3010699

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KEYWORDS

Detection and tracking algorithms

Adaptive control

Design and modelling

Autonomous vehicles

Computer simulations

Mathematical modeling

Motion models

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