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A Bayesian Optimization Approach to Decentralized Event-Triggered Control

Kazumune HASHIMOTO, Masako KISHIDA, Yuichi YOSHIMURA, Toshimitsu USHIO

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Summary :

In this paper, we investigate a model-free design of decentralized event-triggered mechanism for networked control systems (NCSs). The approach aims at simultaneously tuning the optimal parameters for the controller and the event-triggered condition, such that a prescribed cost function can be minimized. To achieve this goal, we employ the Bayesian optimization (BO), which is known to be an automatic tuning framework for finding the optimal solution to the black-box optimization problem. Thanks to its efficient search strategy for the global optimum, the BO allows us to design the event-triggered mechanism with relatively a small number of experimental evaluations. This is particularly suited for NCSs where network resources such as the limited life-time of battery powered devices are limited. Some simulation examples illustrate the effectiveness of the approach.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E104-A No.2 pp.447-454
Publication Date
2021/02/01
Publicized
Online ISSN
1745-1337
DOI
10.1587/transfun.2020MAP0007
Type of Manuscript
Special Section PAPER (Special Section on Mathematical Systems Science and its Applications)
Category

Authors

Kazumune HASHIMOTO
  Osaka University
Masako KISHIDA
  National Institute of Informatics (NII)
Yuichi YOSHIMURA
  Osaka University
Toshimitsu USHIO
  Osaka University

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