Three-dimensional path tracking control for autonomous underwater vehicle based on neural network
基于神经网络的水下机器人三维航迹跟踪控制

Considering the uncertain hydrodynamic coefficients and environmental current disturbances, we propose an adaptive output feedback neural network controller for the three-dimensional path tracking control of an autonomous underwater vehicle (AUV). The controller consists of three control terms: the output feedback control term of the dynamic compensator, the neural network adaptive control term and the robust control term. An observer is designed to provide the neural network with the adaptive learning signal. The stability of the controller is analyzed by Lyapunov theory. A threedimensional path tracking simulation is carried out on an experimental AUV; simulations results show that the designed controller provides high tracking precision, effectively suppresses the effect of the time-varying nonlinear hydrodynamic damping on the AUV system, and significantly attenuate the external currents disturbances.