Convergence Analysis of Remote Iterative Learning Control System with Kalman Filtering ⋆
نویسندگان
چکیده
This article investigates the iterative learning control (ILC) problem for a remote network control systems. To reduce wireless channel noise, a novel method of Kalman filtering is combined into the remote ILC system. The Kalman filtering reduce stochastic error on time axis, while the ILC operates on iteration axis. The convergence of the proposed system was analyzed and the convergence condition is given. Finally, simulation results confirm that the tracking accuracy is improved.
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