Adaptive Zeroing-Gradient Controller for Ship Course Tracking with Near Singularity Considered and Zero Theoretical Tracking Error

Abstract

The zeroing-gradient (ZG) method, a combination of two neural dynamics methods, has been leveraged to construct controller for solving ship course tracking problem with near singularity considered. In this paper, the existing ZG controller is presented and revisited with its limitation identified. Specifically, this paper points out that there exist lagging errors for the ZG controller with the theoretical analyses provided. Then, to remedy the weakness, a new controller is proposed with an adaptive coefficient with zero theoretical tracking errors. Moreover, different activation functions are exploited to accelerate the convergence of the proposed controller. Finally, simulations are conducted to verify the superiority of the proposed controller.