Self-Triggered Model Predictive Control for Nonlinear Input-Affine Dynamical Systems via Adaptive Control Samples Selection

Kazumune Hashimoto, Shuichi Adachi, Dimos V. Dimarogonas

研究成果: Article査読

43 被引用数 (Scopus)

抄録

In this paper, we propose a self-Triggered formulation of model predictive control for continuous-Time nonlinear input-Affine networked control systems. Our control method specifies not only when to execute control tasks but also provides a way to discretize the optimal control trajectory into several control samples, so that the reduction of communication load will be obtained. Stability analysis under the sample-And-hold implementation is also given, which guarantees that the state converges to a terminal region where the system can be stabilized by a local state feedback controller. Some simulation examples validate our proposed framework.

本文言語English
論文番号7423697
ページ(範囲)177-189
ページ数13
ジャーナルIEEE Transactions on Automatic Control
62
1
DOI
出版ステータスPublished - 2017 1

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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