Indirect Adaptive Control for Interconnected Systems with Linear and Nonlinear Parts

Abstract

This paper presents an indirect adaptive control scheme for interconnected systems which also contain linear terms. The system parameters are estimated on-line using a modified recursive least squares algorithm with data normalization. A variable dead zone is incorporated into this estimation algorithm to limit the effects of interconnections and nonlinear dynamics in the system such that the number of the parameters to be estimated is reduced. The adaptive control law consists of a pole placement controller and a nonlinear feedback which compensates the nonlinear dynamics. The proposed adaptive control system is shown to be globally stable. The simulation results on a transputer network for motion control of an industrial robot are given.