Observer-based Neural Network Adaptive Control of Underwater Vehicles

Observer based neural network adaptive control(OBNC) algorithm for underwater vehicles is provided in this paper. The algorithm is composed of three parts: output feedback control, neural network and sliding mode item. Among them, the output feedback control is used to guarantee the stability of the system in initial phase, the neural network is used to approach the nonlinear dynamics of underwater vehicles, and the sliding mode item is used to compensate and bate the internal and external disturbances. The stable conditions and attraction region of the proposed observer based NN control algorithm is provided with Lyapunov based approach. The effectiveness of this control scheme is demonstrated with pool experiment.