Design of a Sliding Mode Controller for the Ship Course Tracking Based on Fuzzy System Parameters Optimization

This paper proposes a fuzzy adaptive sliding mode controller to improve the quality of ship course control through system parameter optimization. First, a sliding mode function is constructed, incorporating adaptive and fuzzy control to approximate the system's switching and uncertain components, respectively. Subsequently, an ergodic method is employed to search for the optimal parameters of the Gaussian function within the fuzzy system according to the designed indicator. Finally, to enhance the interpretability of the controller, six fuzzy rules extracted from human experiences are devised to optimize the parameters of the sliding mode function. The stability of the controller is proved through Lyapunov analysis, and the effectiveness is verified using a training vessel named “Yulong”. The experimental results demonstrate that the proposed controller outperforms pre-optimization model in terms of response time, accuracy and reduction of jitter.