Improved PSO-based S Plane Controller for motion control of underwater vehicle

Abstract

Based on the analysis of fuzzy control, combined with the form of PID control, the S Plane Control has been applied. For the default that particle swarm optimization (PSO) presents the phenomenon of precocity and getting in local minima, the basic PSO algorithm is improved. Based on the self-adaptive idea, a concept of dynamic learning factor is introduced. This method could improve the coordination between global and local searching ability and apt to search out global optimum quickly. Another concept of chasten factor is also introduced, the optimizing ability in PSO algorithm which applied in the S plane algorithm in parameter optimization. Finally, the improved PSO algorithm is applied to the S curve motion control of underwater vehicle. The feasibility and advantages of this method are demonstrated by simulation test results.

Expert S-plane Control of Underwater Vehicle

“…Take [2] for example, precise teacher signal is difficult to get; based on the requirements of hardware velocity and real-time performance, the method in [3] is difficult to put into practice. Because of the deep study of S-plane control, and plenty of experience is accumulated [4], therefore, expert technology [5] can be brought in to enhance the control performance.…”

Stability Analysis on S Plane Control of Underwater Vehicles

“…This method, which combines the benefits of Fuzzy control and PID control, has the advantages of simple structure, few parameters, easy adjustment and convenient application. S Plane Control, which has been improved and optimized [2][3][4][5][6], has been tested in different kinds of underwater vehicles and shows well control capability. Both model tests and real sea trials confirm that this method is suitable for the motion control of underwater vehicles.…”