Adaptive Backstepping Terminal Sliding Mode Control Method Based on Recurrent Neural Networks for Autonomous Underwater Vehicle

作     者：Chao Yang Feng Yao Ming-Jun Zhang 

作者机构：College of Mechanical and Electrical Engineering Harbin Engineering University Harbin 150001 China 

出 版 物：《Chinese Journal of Mechanical Engineering》 (中国机械工程学报（英文版）)

年 卷 期：2018年第31卷第6期

页      面：228-243页

核心收录：

学科分类：12[管理学] 08[工学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0817[工学-化学工程与技术] 081104[工学-模式识别与智能系统] 0807[工学-动力工程及工程热物理] 082402[工学-轮机工程] 0802[工学-机械工程] 0824[工学-船舶与海洋工程] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0801[工学-力学（可授工学、理学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Basic Research Program of Ministry of Industry and Information Technology of China(Grant No.B2420133003) National Natural Science Foundation of China(Grant Nos.51779060,51679054) 

主　　题：Autonomous underwater vehicle(AUV) Trajectory tracking Neural networks Backstepping method Terminal sliding mode Adaptive control 

摘      要：The trajectory tracking control problem is addressed for autonomous underwater vehicle(AUV) in marine environ?ment, with presence of the influence of the uncertain factors including ocean current disturbance, dynamic modeling uncertainty, and thrust model errors. To improve the trajectory tracking accuracy of AUV, an adaptive backstepping terminal sliding mode control based on recurrent neural networks(RNN) is proposed. Firstly, considering the inaccu?rate of thrust model of thruster, a Taylor’s polynomial is used to obtain the thrust model errors. And then, the dynamic modeling uncertainty and thrust model errors are combined into the system model uncertainty(SMU) of AUV; through the RNN, the SMU and ocean current disturbance are classified, approximated online. Finally, the weights of RNN and other control parameters are adjusted online based on the backstepping terminal sliding mode controller. In addition, a chattering?reduction method is proposed based on sigmoid function. In chattering?reduction method, the sigmoid function is used to realize the continuity of the sliding mode switching function, and the sliding mode switching gain is adjusted online based on the exponential form of the sliding mode function. Based on the Lyapu?nov theory and Barbalat’s lemma, it is theoretically proved that the AUV trajectory tracking error can quickly converge to zero in the finite time. This research proposes a trajectory tracking control method of AUV, which can e ectively achieve high?precision trajectory tracking control of AUV under the influence of the uncertain factors. The feasibility and e ectiveness of the proposed method is demonstrated with trajectory tracking simulations and pool?experi?ments of AUV.