Journal of Process Control, Vol.75, 187-203, 2019
Robust constrained model predictive fault-tolerant control for industrial processes with partial actuator failures and interval time-varying delays
This paper studies a robust constrained model predictive fault-tolerant control (RCMPFTC) problem for a class of industrial processes with uncertainties, interval time-varying delay, unknown disturbances and partial actuator failures, in which the main idea is in the relevant theory of RCMPFTC based on a novel extended state space model description of these industrial processes. This extended model includes the state variables and output tracking error variable of process, which actually regulates the dynamic response of the process state and output tracking error separately. Based on this model, the proposed control law is designed, which not only guarantees the convergence and tracking performance of system but also offers more degrees of freedom for designed controller. To ensure robust stability and reject any unknown bounded disturbances for the uncertain system with admissible failures, the optimized cost function and H-infinity performance index are thus introduced in the RCMPFTC controller design. By using a differential inequality to construct a differential Lyapunov-Krasovskii function candidate without introducing some redundant free-weighting matrices, the novel, less conservative and more simplified delay-range-dependent stable conditions of the RCMPFTC design are further presented in terms of linear matrix inequality (LMI) constraints. By solving these LMIs, the RCMPFTC law is explicitly formulated, possessing the optimized cost and H-infinity performance. Furthermore, the stable condition can also be easily extended from delay-range-dependent to common delay-dependent stability. The comparison results on the liquid level of tank system and multi-input and multi-output glasshouse process show that the proposed control method is effective and feasible for the cases of the constant and random-varying actuator faults. (C) 2018 Elsevier Ltd. All rights reserved.