GA-based fuzzy neural network control for ROV

Abstract

Abstract Aiming at the problem of uncertainty and static instability of underwater robot system, a motion control algorithm of underwater robot based on fuzzy neural network optimized by genetic algorithm is proposed in this paper. The algorithm makes use of the characteristics of neural network which can predict and approximate the target value well and the complementarity of fuzzy function to neural network, and uses genetic algorithm to optimize the parameters of fuzzy neural network membership function, so as to reduce the computation of neural network. The experimental results show that the controller has good robustness and enhances the stability of the control system.