A Back Propagation Neural Network Sliding Mode Controller for Ship Course Nonlinear System

摘要

A back propagation network sliding mode variable structure control method is proposed for ship course nonlinear control. 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 sliding mode control. Chattering is greatly reduced and simulation results demonstrate the presented control method has good adaptability and high robustness.