Motion control and path optimization of intelligent AUV using fuzzy adaptive PID and improved genetic algorithm
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Updated: Jul 31, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
Published on: October 14, 2017
Yong Xiong1, Lin Pan2,3,4,5, Min Xiao6
1School of Navigation, Wuhan University of Technology, Wuhan, 430063, China.
Abstract:
This study discusses the application of fuzzy adaptive PID and improved genetic algorithm (IGA) in motion control and path optimization of autonomous underwater vehicle (AUV). The fuzzy adaptive PID method is selected because it is considered to be a strongly nonlinear and coupled system. First, this study creates the basic coordinate system of the AUV, and then analyzes the spatial force from the AUV to obtain the control model of the heading angle, climb angle, and depth. Next, the knowledge of fuzzy adaptive PID and IGA technology on AVU are investigated, then fuzzy adaptive PID controllers and path optimization are established, and experimental simulations are carried out to compare and analyze the simulation results. The research results show that controllers and IGA can be used for the motion control and path optimization of AUV. The advantages of fuzzy adaptive PID control are less overload, enhanced system stability, and more suitable for motion control and path optimization of AUV.
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