An Adversarial Approach to Adaptive Model Predictive Control

Authors

  • Pawel Wachel Department of Control Systems and Mechatronics, Wroclaw University of Science and Technology, Wroclaw, Poland https://orcid.org/0000-0002-7353-2310
  • Cristian R. Rojas School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden https://orcid.org/0000-0003-0355-2663

DOI:

https://doi.org/10.15377/2409-5761.2022.09.10

Keywords:

Linear system, Adaptive control, Multi-armed bandits, Model predictive control, State-space representation

Abstract

This paper presents a novel approach to introducing adaptation in Model Predictive Control (MPC). Assuming limited a priori knowledge about the process, we consider a finite set of possible models (a dictionary), and use the theory of adversarial multi-armed bandits to develop an adaptive version of MPC called adversarial adaptive MPC (AAMPC). Under weak assumptions on the dictionary components, we then establish theoretical bounds on the performance of AAMPC and show its empirical behaviour via simulation examples.

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References

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Published

2022-09-19

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How to Cite

An Adversarial Approach to Adaptive Model Predictive Control. (2022). Journal of Advances in Applied & Computational Mathematics, 9, 135-146. https://doi.org/10.15377/2409-5761.2022.09.10

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