Motion Control of an AUV Using a Neural-Net Based Adaptive Controller

J. Ocean Eng. Technol. 2002;16(1):8-15.

신경회로망 기반의 적응제어기를 이용한 AUV의 운동 제어

이계홍,이판묵,이상정

한국해양연구원 해양시스템안전연구소,한국해양연구원 해양시스템안전연구소,충남대학교 전자공학과

Keywords: Adaptive Control, Sliding Mode Control, Neural Network, Functional Approximation, Underwater Robotic Vehicle, AUV

핵심용어: 적응제어, 슬라이딩 모드 제어, 신경회로망, 함수모사, 수종로봇, 자율무인잠수정

Abstract

This paper presents a neural net based nonlinear adaptive controller for an autonomous underwater vehicle (AUV). AUV's dynamics are highly nonlinear and their hydrodynamic coefficients vary with different operational conditions, so it is necessary for the high performance control system of an AUV to have the capacities of learning and adapting to the change of the AUV's dynamics. In this paper a linearly parameterized neural network is used to approximate the uncertainties of the AUV's dynamic, and the basis function vector of network is constructed according to th AUV's physical properties. A sliding mode control scheme is introduced to attenuate the effect of the neural network's reconstruction errors and the disturbances in AUV's dynamics. Using Lyapunov theory, the stability of the presented control system is guaranteed as well as the uniformly boundedness of tracking errors and neural network's weights estimation errors. Finally, numerical simulations for motion control of an AUV are performed to illustrate the effectiveness of the proposed techniques.