Robust Predictive Fault-Tolerant Control for Multi-Phase Batch Processes With Interval Time-Varying Delay

In view of multi-phase batch processes with interval time-varying delay, uncertainties, unknown disturbances, partial actuator failures and input and output constrains in real-world industrial production, a robust predictive fault-tolerant control (RPFTC) method is proposed in this paper. First, a multi-phase batch process considering the above process dynamics is described by a switching model that consists of different dimensional sub-systems. Then the switching model is transformed into the extended switching state space model by the introduction of output tracking error. On basis of this extended model, a robust predictive fault-tolerant control law is designed to improve the control performance and to obtain more degrees of freedom of the adjustment for the controller. Second, by the utilization of Lyapunov function theory, switching system theory and average dwell time approach, the sufficient conditions in terms of linear matrix inequality (LMI) constraints and minimum running time at each phase are given to make the corresponding discrete-time switching closed-loop system robustly exponential stable and the running time of each phase shortest. At the same time, the optimal cost function and H-infinity performance index are considered in the derivation of stable conditions, which can obtain the optimized control performance and suppress the unknown disturbances. Finally, the gain of the control law and the minimum running time of each phase are calculated by solving these LMIs. Taking the injection molding process as a simulation object, the control results verify the effectiveness and feasibility of the proposal.