Robust sampled-data control

Abstract

Robust control of uncertain plants is a major area of interest in control theory. In this dissertation, robust stabilization of plants under various classes of structural perturbations using sampled-data controllers is considered. It is shown that a controllable system under bounded perturbations that satisfy certain structural conditions can be stabilized using high-gain sampled-data state feedback control, provided that the sampling period is sufficiently small, with generalizations to decentralized control of interconnected systems. This result is then modified so as to enable adapting the gain and the sampling periods of controllers online. Finally another design methodology is given which enables the controllers to operate on the sampled values of output only, instead of full state measurements.