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A method of Kalman filtering for remote iterative learning control system with wireless channel noise

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4 Author(s)
Wenju Zhou ; Sch. of Mechatron. Eng. & Autom., Shanghai Univ., Shanghai, China ; Minrui Fei ; Xiaobing Zhou ; Zhe Li

In this paper, the iterative learning control (ILC) problem is considered for a class of remote control system through wireless network communication channels. A novel Kalman filtering used in remote ILC system with wireless channel noise is presented. The theory that ILC eliminates repeating disturbances is analyzed in detail. A new idea of connecting every iteration trail owning fixed interval time as a whole which acquires infinite time is firstly proposed. The Kalman filtering estimates stochastic error value on this infinite time axis, while the ILC operates on iteration axis which is orthogonal with time axis. Finally, the results of experiments obtained under the cases of ILC and Kalman filtering show that the tracking accuracy is greatly improved with the proposed new method.

Published in:

Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on

Date of Conference:

19-21 Oct. 2011