Decentralized Robust Adaptive Control Of Nonlinear Systems Represented By Input-Output Models

Many practical systems such as power systems, robot manipulators and biochemical processes are multiple-input-multiple-output nonlinear systems with various uncertainties. These uncertainties include unknown disturbances, structural uncertainties, parametric uncertainties and unmodeled dynamics. The adaptive control of nonlinear systems has emerged as an active research area recent years. Various adaptive control schemes have been proposed. However, most of these schemes are based on state feedback and deal with single-input-single-output systems. Unmodeled dynamics are not considered or parameter estimation is needed in some of these schemes presented in literatures. Compared with centralized control, decentralized adaptive control is dispersive in danger and it is more reliable and economical. Therefore, decentralized adaptive control of multiple-input-multiple-output nonlinear systems with uncertainties is interesting and important both in theory and practical applications.In this paper, a decentralized robust adaptive control scheme is proposed for a class of multiple-input-multiple-output systems with nonlinear parameterization represented by input-output models. With the proposed control scheme, all the variables of the closed-loop systems...