Iterative Learning Control for Actuator Fault Uncertain Systems

An iterative learning fault-tolerant control method is designed for an actuator fault intermittent process with simultaneous uncertainties the system parameters. First, tolerance controller using 2D theory, and (ILC) transformed into a Roesser model. Secondly, sufficient conditions controller’s existence are analyzed linear matrix inequality (LMI) technique, gain matrices obtained by convex optimization LMI constraints. Under these all additive parameters admissible failures, can ensure closed-loop performance in both time batch directions, it also meet H∞ robust level against outside disturbances. Eventually, algorithm’s computational complexity analyzed, effectiveness of algorithm verified simulation respect to injection molding machine Compared traditional ILC laws, which do not consider faults, proposed has better convergence speed stability when time-invariant time-variant faults occur during implementation.