Robust model predictive control of discrete nonlinear systems with time delays and disturbances via T–S fuzzy approach. (May 2017) - Teng, Long; Wang, Youyi; Cai, Wenjian; Li, Hua
Abstract : Highlights: Model predictive control (MPC) of discrete systems with multiple delays and disturbances is investigated simultaneously. New conditions of robust positive invariance (RPI) and input-to-state stability (ISS) under disturbances are proposed for MPC of a class of discrete time-delay systems. Robust fuzzy model predictive control (RFMPC) for time-delay systems is investigated and applied to the process systems. Abstract: In this paper, robust fuzzy model predictive control of a class of nonlinear discrete systems subjected to time delays and persistent disturbances is investigated. Based on the modeling method of delay difference inclusions, nonlinear discrete time-delay systems can be represented by T–S fuzzy systems comprised of piecewise linear delay difference equations. Moreover, Lyapunov–Razumikhin function (LRF), instead of Lyapunov–Krasovskii functional (LKF), is employed for time-delay systems due to its ability to reflect system original state space and its advantages in controller synthesis and computation. The robust positive invariance and input-to-state stability with respect to disturbance under such circumstances are investigated. A robust constraint set is adopted that the system state is converged to this set round the desired point. In addition, the controller synthesis conditions are derived by solving a set of matrix inequalities. Simulation results show that the proposed approach can be successfully applied to the well-known continuous stirred tank reactor (CSTR) systems subjected to time delay.