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

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.