Nonlinear Model Predictive Control Using Successive Linearization

Application to Chemical Reactors

Abstract

A nonlinear model predictive control based on successive linearization approach is developed. A nonlinear process model is linearized along its trajectory and an infinite-time horizon linear optimal regulator with integrator is implemented in a receding horizon fashion. Simulation examples for highly nonlinear chemical reactors which exhibit static input or output multiplicities are given to demonstrate the capability of the controller. The developed control algorithm has been successfully applied to a grade transition operation in an industrial polymerization reactor.