Iterative learning control for discrete-time systems with missing measurements

For packet-based transmission of data over a network, or temporary sensor failure, etc., data samples may be missing in the measured signals. This paper deals with the problem of iterative learning controller design for linear discrete time systems with missing measurements. The missing measurements will happen at any sample time, and the probability of the occurrence of missing data is assumed to be known. The iterative learning controller is developed to guarantee the convergence of the tracking error and with quadratic performance index. A numerical example is provided to demonstrate the validity of the proposed design approach