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Predictive control for discrete-time system with nonlinearity and multiple missing measurements

In this paper, we discuss the predictive control problem for discrete-time system with nonlinearity and multiple missing measurements. A series of mutually independent random variables satisfying certain probabilistic distribution is used to model the multiple missing-measurements. We introduce a new strategy to compensate the negative effects from the missing measurements. The aim is to investigate the controller synthesis based on the predictive control idea. It is shown that the proposed predictive design method can achieve the desired performance requirements of the closed-loop system. Finally, we provide a simulation to illustrate the feasibility of the designed control algorithm.