PSO Optimization-Based Series-Level Fuzzy PID Underwater Robot Fixed Depth Control

Abstract

A series-level fuzzy PID control method based on PSO optimization is proposed for ROV constant depth control to address the problems of long adjustment time and poor robustness of traditional PID controllers in ROV motion control. The kinematic and dynamic analysis of the six-degree-of-freedom ROV is carried out to obtain the mathematical model of the ROV motion with a fixed depth. The optimal values of the controller parameters are obtained by optimizing the controller parameters with the improved particle swarm algorithm under the string-level fuzzy PID control conditions. The effect of the control algorithm is verified by simulation. The results show that the series-level fuzzy PID control based on PSO optimization has significant advantages over traditional control methods, with strong anti-interference capability, minor overshoot, and shorter adjustment time.