완전 궤환형의 비선형 시스템에 대한 신경회로망기반의 강인한 적응제어

Abstract

This paper considers the neural network adaptive control design problems for the nonlinear systems in strict-feedback form with unbounded exogenous input terms. So far, robust adaptive control methods have been applied only to a relatively simple case where the unstructured uncertainties are assumed be bound, although the constant bounds may be unknown. In this paper, the only required priori information about exogenous input terms is that they are satisfying certain Lipschitz conditions with unknown Lipschitz constants. Under these relaxed assumptions, the proposed control scheme can guarantee that all the signals in the closed-loop are UUB. Some practical features of the proposed control law are also discussed.