AUV course angle control method based on PPGA self-adaptive optimization PID parameters

Abstract

The invention provides an AUV (Autonomous Underwater Vehicle) course angle control method based on PPGA (Point-to-Point Graphics Array) self-adaptive optimization PID (Proportion Integration Differentiation) parameters. In order to solve the problems of slow response speed and uncertain parameters of the traditional PID method and the problems of easy premature phenomenon and slow convergence speed of the traditional genetic algorithm optimization, three optimal PID parameters in the control system are searched through a pseudo-parallel genetic algorithm so as to achieve course angle motion control of the AUV. The algorithm has good global optimization capability, and can find out an optimal solution in a feasible region through genetic optimization to obtain an optimal control scheme, thereby greatly improving the efficiency and precision of the controller.

Description

technical field [0001] The invention relates to an AUV heading angle control method based on PPGA self-adaptive optimization of PID parameters, belonging to the field of AUV control. Background technique [0002] In recent decades, autonomous underwater vehicles (AUVs) have received extensive attention and many related results have been achieved. An autonomous underwater vehicle (AUV) is an underwater vehicle that has its own energy source and relies on its autonomy to manage and control itself to complete predetermined tasks. It can be used for marine scientific investigations, port security monitoring, underwater search and rescue, and naval applications. deployment etc. Motion control technology is one of the key technologies of underwater robots, and good motion control technology is the premise and guarantee for underwater robots to complete specific tasks. With the expansion of the application range of underwater robots, the requirements for autonomy, precision and s...

AI Technical Summary

Problems solved by technology

[0003] At present, the AUV motion control technologies mainly used include: PID control, fuzzy control, genetic algorithm optimization PID control, etc. The traditional PID control algorithm is the most widely used control algorithm at present, but it has slow response, easy overshoot, and poor anti-interference ability. and other shortcomings

The choice of many fuzzy variables and membership functions in fuzzy control requires expert experience knowledge that has been verified by practice to guide the design. There is no experience to use for a new design of fuzzy variables; The adaptation process takes time, especially when the amplitude and cycle of the external disturbance are similar to the motion amplitude and cycle of the underwater robot, the learning of the neural network will lag behind, causing the control to oscillate

Images