Data-based internal model controller design for a class of nonlinear systems

Abstract

An Internal Model Control (IMC) design strategy is proposed for a class of nonlinear systems that can be described by data-based modeling technique called Just-in-Time Learning (JITL). The proposed controller consists of a conventional linear controller augmented by a series of correction terms to account for nonlinearities in the system. The resulting controller is shown to have superior performance when compared with a linear IMC controller. This is evaluated by a case study of a polymerization reactor. © 2005 IEEE.