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An improved robust model predictive control approach to systems with linear fractional transformation perturbations

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Abstract

In this paper, a robust model predictive control approach is proposed for a class of uncertain systems with time-varying, linear fractional transformation perturbations. By adopting a sequence of feedback control laws instead of a single one, the control performance can be improved and the region of attraction can be enlarged compared with the existing model predictive control (MPC) approaches. Moreover, a synthesis approach of MPC is developed to achieve high performance with lower on-line computational burden. The effectiveness of the proposed approach is verified by simulation examples.

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Authors and Affiliations

  1. Department of Automation, Shanghai Jiao Tong University, Shanghai, 200240, PRC

    Peng-Yuan Zheng, Yu-Geng Xi & De-Wei Li

  2. Key Laboratory of System Control and Information Processing, Ministry of Education, Beijing, PRC

    Peng-Yuan Zheng, Yu-Geng Xi & De-Wei Li

Authors
  1. Peng-Yuan Zheng
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  2. Yu-Geng Xi
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  3. De-Wei Li
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Corresponding author

Correspondence to Peng-Yuan Zheng.

Additional information

This work was supported by National Natural Science Foundation of China (No. 60934007, No. 61074060), China Postdoctoral Science Foundation (No. 20090460627), Shanghai Postdoctoral Scientific Program (No. 10R21414600), and China Postdoctoral Science Foundation Special Support (No. 201003272).

Peng-Yuan Zheng received his B. Sc. degree in electrical engineering and automation from the North University of China, PRC in 2000, the M. Sc. degree in measurement technology and instrumentation from University of Shanghai for Science and Technology, Shanghai, PRC in 2005. He is currently a Ph.D. candidate in the Department of Automation at Shanghai Jiao Tong University, PRC.

His research interests include predictive control and robust control.

Yu-Geng Xi received the Dr.-Ing. degree in automatic control from the Technical University Munich, Germany in 1984. Since then, he has been with the Department of Automation, Shanghai Jiao Tong University, and as a professor since 1988.

His research interests include predictive control, large scale and complex systems, and intelligent robotic systems.

De-Wei Li received the B. Sc. degree in automation from Shanghai Jiao Tong University, Shanghai, PRC in 1993, the Ph.D. degree in control theory and control engineering from Shanghai Jiao Tong University, Shanghai, PRC in 2009. He is currently a postdoctoral research fellow in Shanghai Jiao Tong University.

His research interests include predictive control and robust control.

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Zheng, PY., Xi, YG. & Li, DW. An improved robust model predictive control approach to systems with linear fractional transformation perturbations. Int. J. Autom. Comput. 8, 134–140 (2011). https://doi.org/10.1007/s11633-010-0565-x

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  • DOI: https://doi.org/10.1007/s11633-010-0565-x

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