Sliding Mode Control Method of Autonomous Underwater VehicleBased on Neural Network
Considering the traditional sliding mode controller's chattering during the control of Autonomous Underwater Vehicle(AUV)and the adverse effects of actuator saturation on control performance,a sliding mode control method based on neural network has been proposed.The Radial Basis Function Neural Network(RBFNN)and adaptive observer are used to estimate the uncertain terms and unknown external disturbances in the motion model online to reduce sliding mode chattering.At the same time,the RBFNN is used to ap-proximate the difference between the control inputs before and after being restricted to overcome the control oscillation caused by actuator saturation.The numerical simulation shows that this control method has better adaptability and control accuracy compared with traditional sliding mode control.
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维普
