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Remote Iterative Learning Control System with Duplex Kalman Filtering

  • Wenju Zhou
  • Minrui Fei
  • Haikuan Wang
  • Xiaobing Zhou
  • Lisheng Wei
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 324)

Abstract

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.

Keywords

Wireless network control systems Remote iterative learning control (RILC) Kalman filtering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Wenju Zhou
    • 1
    • 2
  • Minrui Fei
    • 1
  • Haikuan Wang
    • 1
  • Xiaobing Zhou
    • 1
  • Lisheng Wei
    • 3
  1. 1.Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and AutomationShanghai UniversityShanghaiChina
  2. 2.School of Information and Electronic EngineeringLudong UniversityYantaiChina
  3. 3.School of Information and Electronic EngineeringAnhui Polytechnic UniversityWuhuChina

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