Networked Iterative Learning Control for Nonlinear Switched Discrete-time Systems with Random Measurement Packet Losses

For nonlinear switched discrete-time systems with random measurement packet losses modeled by a Bernoulli-type stochastic sequence, this paper presents a P-type networked Iterative Learning Control (ILC) algorithm with an attenuating forgetting factor. In this ILC scheme, the random measurement packet losses are replaced by the desired output data. Under a given switching rule, the convergence of ILC tracking error in mathematical expectation in each of subsystems is proved by mathematical induction, and the convergent condition of the proposed networked P-type ILC algorithm is given. An illustrative simulation is used to verify the effectiveness of the proposed ILC algorithm.