Remote Iterative Learning Control System with Duplex Kalman Filtering

This article investigates the iterative learning control (ILC) problem for a remote network control systems under wireless network condition. To reduce wireless channel noise, a novel method of duplex Kalman filtering is firstly presented and combined into the remote ILC system. The convergence of system is analyzed and the convergence condition is given. The merit of the propose method is also verified by comparing the fluctuations boundaries of the two cases with Kalman filtering and without Kalman filtering. Finally, simulation results confirm that the tracking accuracy is greatly improved in comparison with other approaches under different cases of ILC and Kalman filtering.