A Data-driven Optimal Iterative Learning Control with Data Loss Compensation

In this work, a control scheme with compensation along the iteration axis is discussed for discrete time nonlinear systems with random data loss. The loss of output data from sensor to controller is considered, and the data missing is described through a variable satisfying the Bernoulli distribution. The lost output value is estimated by using the time-varying parameter and the output value of the last iteration to compensate the influence of data loss on the plant. A numerical simulation example verifies the validity of the algorithm.