A BP Neural Network Variable Structure Controller for Ship Course Nonlinear System

摘要

A Back Propagation (BP) neural network variable structure control method is proposed for nonlinear control of ship course. Back propagation neural network is used to simulate the functional relation between state hyperplane of the system and the exponential reaching law. A hyperbolic tangent function is applied to replace the saturation function to realize the boundary method of variable structure control. Chattering is greatly weakened and simulation results demonstrate the presented control method has good adaptability and high robustness.