2입력 2출력 비선형시스템을 위한 강인한 신경회로망 제어기법

Abstract

This paper presents a robust neural network control scheme for diving behavior of an autonomous under- water vehicle (AUV) whose diving dynamics can be simplified as a second-order TITO (two-input-two-output) nonlinear function. Because of singularity problem, above dynamics could not be properly solvable using general backstepping method although it is in a well known strict-feedback form. Furthermore, the dynamics is in an interactive form so the traditional noninteracting control methods also could not be directly applied. In this paper, the desired value of one of two virtual inputs is derived from predefined desired trajectory of the vehicle instead of stability point of view so that the singularity problem could be avoided. Proposed scheme can guarantee all of the signals in the closed-loop system are uniformly ultimately bounded (UUB).