Analysis and control of nonlinear systems with uncertainties by feedback linearization

Abstract

In this thesis we focus on feedback linearization control. Traditionally, feedback linearization has been limited in dealing with nonlinear systems which have uncertainties in their system models. Our main topic is to improve the robustness of feedback linearization to overcome uncertainty problems. We provide the estimation of error bound caused by any uncertainty in the model and also suggest an analytic relation between system``s stability and the magnitude of uncertainty. An integrator is added to a controller and its effect is shown analytically. Based on those results, we show various ways to apply feedback linearization to wider range of systems. Then, we switch our concern to input-output feedback linearization and propose a robust feedback linearization control law. Finally, the proposed control law is applied to electromagnetic suspension system.