신경회로망 적응제어기를 이용한 자율무인잠수정(AUV)의 운동제어

Abstract

This paper presents a neural network adaptive controller for autonomous underwater vehicles (AUVs). A linearly parameterized neural network (LPNN) is used to approximate the nonlinear uncertainties of AUVs’ dynamics, where the basis function vector of LPNN is constructed according to the physical properties of AUVs. A sliding mode control scheme is adopted to attenuate the effects of net-work’s reconstruction errors and disturbances in AUV’s dynamics. The asymptotic convergence of AUV’s tracking errors and the stability of the presented control system are guaranteed on the basis of Lyapunov theory. Numerical simu-lation studies for motion control of an AUV are performed to illustrate the effectiveness of the proposed controller.