Pole Placement-Based NMPC of Hammerstein Systems and Its Application to Grade Transition Control of Polypropylene

Abstract EN

This paper presents a new nonlinear model predictive control (MPC) algorithm for Hammerstein systems subject to constraints on the state, input, and intermediate variable.

Taking no account of constraints, a desired linear controller of the intermediate variable is obtained by applying pole placement to the linear subsystem.

Then, actual control actions are determined in consideration of constraints by online solving a finite horizon optimal control problem, where only the first control is calculated and others are approximated to reduce the computational demand.

Moreover, the asymptotic stability can be guaranteed in certain condition.

Finally, the simulation example of the grade transition control of industrial polypropylene plants is used to demonstrate the effectiveness of the results proposed here.