Self-triggered Model Predictive Control for continuous-time systems: A multiple discretizations approach

Kazumune Hashimoto, Shuichi Adachi, Dimos V. Dimarogonas

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

In this paper, we propose a new self-triggered formulation of Model Predictive Control for continuous-time linear networked control systems. Our control approach, which aims at reducing the number of transmitting control samples to the plant, is derived by parallelly solving optimal control problems with different sampling time intervals. The controller then picks up one sampling pattern as a transmission decision, such that a reduction of communication load and the stability will be obtained. The proposed strategy is illustrated through comparative simulation examples.

本文言語English
ホスト出版物のタイトル2016 IEEE 55th Conference on Decision and Control, CDC 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ページ3078-3083
ページ数6
ISBN(電子版)9781509018376
DOI
出版ステータスPublished - 2016 12 27
イベント55th IEEE Conference on Decision and Control, CDC 2016 - Las Vegas, United States
継続期間: 2016 12 122016 12 14

Other

Other55th IEEE Conference on Decision and Control, CDC 2016
CountryUnited States
CityLas Vegas
Period16/12/1216/12/14

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Control and Optimization

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