Nonlinear parametric predictive control. Application to a continuous stirred tank reactor

Abstract

This paper presents a nonlinear model‐based controller based on the ideas of parametric predictive control applied to a continuous stirred tank reactor (CSTR) process unit. Controller design aims at avoiding the complexity of implementation and long computational times associated with conventional NMPC while maintaining the main advantage of taking into account process nonlinearities that are relevant for control. The design of the parametric predictive controller is based on a rather simplified process model having parameters that are instrumental in determining the required changes to the manipulated variables for error reduction. The nonlinear controller is easy to tune and can operate successfully over a wide range of operating conditions. The use of an estimator of unmeasured disturbances and process‐model mismatch further enhances the behavior of the controller.