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Intelligent control using multiple models based on on-line learning

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Abstract

In this paper we deal with the problem of plants with large parameter variations under different operating modes. A novel intelligent control algorithm based on multiple models is proposed to improve the dynamical response performance. At the same time adaptive model bank is applied to establish models without prior system information. Multiple models and corresponding controllers are automatically established on-line by a conventionally adaptive model and a re-initialized one. A best controller is chosen by the performance function at every instant. The closed-loop system’s stability and asymptotical convergence of tracking error can be guaranteed. Simulation results have confirmed the validity of the proposed method.

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Authors and Affiliations

  1. Research Institute of Automation, Southeast University, Nanjing, Jiangsu, 210096, China

    Junyong Zhai, Shumin Fei & Feipeng Da

Authors
  1. Junyong Zhai
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  2. Shumin Fei
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  3. Feipeng Da
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Additional information

This work was partly supported by National Natural Science Foundation of China (No. 60574006); the Specialized Research Fund for Doctoral Program of Higher Education of China (No. 20030286013); Provincial Natural Science Foundation of Jiangsu (No. BK2003405) and Graduate Innovative Project of Jiangsu Province (2005).

Junyong ZHAI was born in 1977. He is a Ph.D. candidate at the Research Institute of Automation, Southeast University. His current research interests include multiple models switching control and adaptive control.

Shumin FEI was born in 1961. He received the Ph.D. degree from Beihang University in 1995. From 1995 to 1997, he did postdoctoral research in the Research Institute of Automation at Southeast University. He now is a professor in the Research Institute of Automation at Southeast University, Nanjing. His research interests include analysis and synthesis of non-linear systems, robust control, adaptive control and analysis and synthesis of time-delay systems and so on.

Feipeng DA received the Ph.D. degree from Southeast University in 1998. During 1998–2000, he worked as postdoctoral research fellow in Southeast University and Jin Cheng Group. Since 2000, he has been with the Research Institute of Automation, Southeast University, where he is currently Professor. His research interests include neural networks, adaptive fuzzy systems, evolutionary computation, sliding mode and intelligent control, reverse engineering and 3D reconstruction.

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Zhai, J., Fei, S. & Da, F. Intelligent control using multiple models based on on-line learning. J. Control Theory Appl. 4, 397–401 (2006). https://doi.org/10.1007/s11768-006-5153-9

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  • DOI: https://doi.org/10.1007/s11768-006-5153-9

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