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A filtering based multi-innovation extended stochastic gradient algorithm for multivariable control systems

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  • Control Theory and Applications
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Abstract

For a multivariable system with moving average noise (i.e., a multivariable controlled autoregressive moving average system), this paper proposes a filtering based extended stochastic gradient (ESG) algorithm and a filtering based multi-innovation ESG algorithm for improving the parameter estimation accuracy. The key is using the filtering technique and the multi-innovation identification theory. The proposed algorithms can identify the parameters of the system model and the noise model. The filtering based multi-innovation ESG algorithm can give more accurate parameter estimates. The numerical simulation results demonstrate that the proposed algorithms work well.

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan, 430068, PR China

    Jian Pan, Xiao Jiang, Xiangkui Wan & Wenfang Ding

Authors
  1. Jian Pan
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  2. Xiao Jiang
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  3. Xiangkui Wan
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  4. Wenfang Ding
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Corresponding author

Correspondence to Jian Pan.

Additional information

Recommended by Associate Editor Jiuxiang Dong under the direction of Editor Duk-Sun Shim. This work was supported by the National Natural Science Foundation of China (No. 61571182). The authors are grateful to Professor Feng Ding at the Jiangnan University (Wuxi, China) and the main idea of this work is from him and his book “System Identification–Multi-Innovation Identification Theory and Methods, Beijing: Science Press, 2016”.

Jian Pan was born in Wuhan, China. He received the B.Sc. degree from the Hubei University of Technology in 1984. Since 1984, he is with the Hubei University of Technology, Wuhan, China and he is currently an aasociate professor and a master supervisor. He is currently a director of Hubei Association of Automation and a director of Wuhan Power Supply Society. His currently research interests include control science and engineering, computer control systems, power electronics.

Xiao Jiang was born in Jingzhou, Hubei Province in December, 1991. She received her B.Sc degree in School of Electrical Engineering and Automation from Wenhua College (Wuhan, China) in 2014. She is currently a master student in School of Electrical and Electronic Engineering at the Hubei University of Technology (Wuhan, China). Her research interests include system Identification and process control.

Xiangkui Wan received the M.S. and Ph.D. degrees in the Mechatronic Engineering from Chongqing University in 2002 and 2005, respectively. He is currently a professor in the School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan, China. His research interests include digital signal processing, biomedical signal processing and analysis, biomedical modeling and simulation, cardiovascular system. p ]Wenfang Ding received the M.Eng. degree in the Electrical Engineering from Hubei University of Technology in 1992. He is an associate professor in the School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan, China. His research interests include electrical automation and systems and modern power electronics technology.

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Pan, J., Jiang, X., Wan, X. et al. A filtering based multi-innovation extended stochastic gradient algorithm for multivariable control systems. Int. J. Control Autom. Syst. 15, 1189–1197 (2017). https://doi.org/10.1007/s12555-016-0081-z

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  • DOI: https://doi.org/10.1007/s12555-016-0081-z

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