Chapter 18 - Optimal state estimation for nonlinear control of complex dynamic systems

Abstract

Optimal state estimation has received considerable significance in the control of complex nonlinear dynamical systems that are characterized by input–output multiplicities, parametric sensitivity, nonlinear oscillations, and chaos. In this study, a nonlinear internal model control (NIMC) strategy that incorporates the nonlinear model structure and the estimator dynamics in the control law is presented for the control of nonlinear dynamical systems. The state estimator is designed to provide the unmeasured process states that capture the fast-changing nonlinear dynamics of the process to incorporate in the controller. The performance of the estimator-supported NIMC strategy is evaluated by applying it for the control of a nonisothermal nonlinear chemical reactor and a homopolymerization reactor, which exhibit rich dynamical behavior ranging from stable situations to chaos. The results evaluated under different conditions show the better performance of the estimator-based NIMC strategy over the conventional controllers.