Discrete‐Time nonlinear control of processes with actuator saturation

Abstract

This note presents discrete-time nonlinear model-based control laws for multivariable processes with actuator saturation. This work is a continuation of the nonlinear controller synthesis results for unconstrained processes (Soroush and Kravaris, 1996). The control laws presented in this note are input-output linearizing in the absence of input constraints, can provide significant improvement in control quality in the presence of active input constraints, and are model-predictive in the sense that they are exact solutions to a moving-horizon optimization problem. The connections between the derived control laws and (a) model state feedback control (Coulibaly et al., 1995) and (b) modified internal model control (IMC) (Zheng et al., 1994) are explained briefly. This note begins with a description of the scope of the work. Dynamic control laws are derived first for processes with full state measurements and then for processes with incomplete state measurements. The application and performance of one of the nonlinear control laws are demonstrated by a chemical reactor example.