Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels

Abstract

This paper develops a novel adaptive neural integral sliding-mode control to enhance the tracking performance of fully actuated uncertain surface vessels. The proposed method is built based on an integrating between the benefits of the approximation capability of neural network (NN) and the high robustness and precision of the integral sliding-mode control (ISMC). In this paper, the design of NN, which is used to approximate the unknown dynamics, is simplified such that just only one simple adaptive rule is needed. The ISMC, which can eliminate the reaching phase and offer higher tracking performance compared to the conventional sliding-mode control, is designed such that the system robust against the approximation error and stabilize the whole system. The design procedure of the proposed controller is constructed according to the backstepping control technique so that the stability of the closed-loop system is guaranteed based on Lyapunov criteria. The proposed method is then tested on a simulated vessel system using computer simulation and compared with other state-of-the-art methods. The comparison results demonstrate the superior performance of the proposed approach. KEYWORDSadaptive control, backstepping control technique, integral sliding-mode control, neural network, surface vessels Int J Robust Nonlinear Control. 2019;29:1537-1557. wileyonlinelibrary.com/journal/rnc

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