Robust switched predictive control for multi-phase batch processes with uncertainties and unknown disturbances

Abstract

A robust switched predictive control method is designed to deal with the multi-phase batch processes with the inevitable uncertainties, time-varying delay and unknown disturbances. Firstly, the output tracking errors are augmented into the state variables and then the improved robust switched predictive control law is established using the new augmented state variables. To this end, the novel switched system is built to represent the different phases of multi-phase batch processes. Secondly, making full use of the robust predictive control theory, Lyapunov function theory, switched system theory, linear matrix inequality (LMI) theory and mode-dependent average dwell time method, the sufficient conditions in terms of LMI constraints are derived to ensure that the switching system is asymptotically controllable and stable. During the process of derivation, based on the traditional performance indicators, the H-infinite performance index is introduced, so that the system in different phases can still operate stably under the uncertainty and external interference. The average dwell time and the control law gain of each phase are thus calculated by solving these LMI constrains. Ultimately, the simulation results on the injection molding process show that the proposed method can make the controlled system run stably.