IJCAS

This paper investigates memory nonfragile mixed-objective output feedback robust model predictive control (OFRMPC) for a class of uncertain systems subjected to physical constraint, bounded disturbance, unmeasurable delayed state and possible controller fragility. By employing a delay-independent Lyapunov-Krasovskii function and linear matrix inequality (LMI) framework, novel sufficient conditions for the proposed memory nonfragile OFRMPC are derived to asymptomatically stabilize the closed-loop system with guaranteed H∞/H2 performance for all admissible polytopic uncertainties, external disturbance, state delay, and additive or multiplicative gain perturbation. A key technique for this controller is the online optimization of an infinite-horizon objective function followed by a memory output feedback control law based on the pre-specified offline state estimator using modified quadratic bounded conditions. Moreover, the input constraint and the recursive feasibility have been further guaranteed via additional LMI-based conditions. Finally, a numerical example is given to illustrate the effectiveness of the proposed OFRMPC approach.

Keywords: Linear matrix inequality, model predictive control, nonfragile, output feedback.