Supercavitating Vehicle LSSVM Multiple Intelligent Control

Abstract

According to the conditions of supercavitating vehicle stable control problems, the massive uncertain factors caused by reactions between the vehicle and cavity, and the control system real-time request, the paper presents a supercavitating vehicle stable navigation least squares support vector multiple intelligent control scheme. The scheme makes full use of the nonlinear mapping ability, self-learning adaptability and parallel information processing of the least squares support vector machine. Combining with fuzzy control method, complementary advantages, the closed-loop control has been formed. The simulation shows that the control system has good adaptive ability and robustness. The supercavitating movement stability and precise control realizes even in the situation that difficult to obtain an accurate model.