Observer-based robust model predictive control of a class of nonlinear systems with both state and input delays

This paper presents an observer-based robust model predictive control (RMPC) for a class of nonlinear systems with both state and input delays. The observer is invoked to estimate the states of system when the states are not completely measurable. The MPC problem is formulated with a memory-less observer-based feedback control law to minimize the upper bound of the infinite horizon cost that satisfies the sufficient stability conditions. Novel delay dependent sufficient conditions are proposed for the existence of such controllers in the form of a linear matrix inequality (LMI) optimization problem. A numerical example is included to illustrate the effectiveness of the proposed method.