A discrete iterative learning control of nonlinear time-varying systems

A discrete iterative learning control is presented for MIMO discrete nonlinear time-varying systems with initial state error, input disturbance and output measurement noise. A feedforward learning algorithm is designed under a feedback configuration and is updated by more than one past control data, in the previous trials. A systematic approach is developed to analyze the robustness and convergence of the proposed learning scheme. It is shown that the learning algorithm not only solves the robustness problem but also improves the learning rate for discrete nonlinear time-varying systems.