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More relaxed conditions for model predictive control with guaranteed stability

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Abstract

For the model predictive controller, terminal state satisfying a certain inequality can guarantee the stability but it is somewhat conservative. In this paper, we give a more relaxed stability condition by considering the effect of the initial state. Based on that we propose an algorithm to guarantee that the closed loop system is asymptotically stable. Finally, the conclusions are verified by a simulation.

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Authors and Affiliations

  1. Institute of Automation, Shanghai Jiaotong University, 200030, Shanghai, China

    Bin Liu & Yugeng Xi

Authors
  1. Bin Liu
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  2. Yugeng Xi
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Additional information

This work was supported by the National Natural Science Foundation (No. 69934020).

Bin LIU was born in 1975. He received the Bachelor degree from the Taiyuan Heavy Mechinary Institute in 1998 and now is a Ph. D. candidate in the Automation Institute of Shanghai Jiao-tong University. His research interests include the stability and robustness of model predictive control.

Yugeng XI was born in 1946. He received the Bachelor degree from the Harbin Military Engineering Institute in 1968 and Ph. D. degree in engineering from the Munich Industry University. He is now a professor with the Automation Institute of Shanghai Jiaotong University. His research interests include the optimization control in the I complex industry process, intelligent robot control and rolling scheduling.

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Liu, B., Xi, Y. More relaxed conditions for model predictive control with guaranteed stability. J. Control Theory Appl. 3, 189–194 (2005). https://doi.org/10.1007/s11768-005-0015-4

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  • DOI: https://doi.org/10.1007/s11768-005-0015-4

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