Applications of Adaptive Controllers to Systems With Nonlinear Parametrization

Abstract

Nonlinear parametrizations occur in dynamic models of several complex engineering problems. The theory of adaptive estimation and control has been applicable, by and large, to problems where parameters appear linearly. We have recently developed an adaptive controller that is capable of estimating parameters that appear nonlinearly in dynamic systems in a stable manner. In this paper, we present this algorithm and its applicability to two problems, temperature regulation in chemical reactors and precise positioning using magnetic bearings both of which contain nonlinear parametrizations. It is shown in both problems that the proposed controller leads to a significantly better performance than those based on linear parametrizations or linearized dynamics.