Model based predictive control for a system with long time delay

Koji Kobayashi, Yutaka Uchimura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a control method that compensates the time delay in a system by predicting the future states of a plant. The proposed method contains a state predictor that predicts the future values of a system. Furthermore, the proposed method considers the uncertainty in a model in terms of modeling error, which might cause the predicted value to degrade the performance of the system or even destabilize it in the worst case. The disturbance in a remote plant is explicitly considered and is compensated by placing a feedback controller on the remote side. This paper describes the proposed control method based on model-based predictive control that considers modeling error. Furthermore, this paper describes a method of designing a feedback controller based on the H norm. The stability of the proposed system is analyzed, and the performance of the method is evaluated and compared with a conventional methods using numerical simulation results.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE 15th International Workshop on Advanced Motion Control, AMC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages581-586
Number of pages6
ISBN (Electronic)9781538619469
DOIs
Publication statusPublished - 2018 Jun 1
Event15th IEEE International Workshop on Advanced Motion Control, AMC 2018 - Tokyo, Japan
Duration: 2018 Mar 92018 Mar 11

Publication series

NameProceedings - 2018 IEEE 15th International Workshop on Advanced Motion Control, AMC 2018

Other

Other15th IEEE International Workshop on Advanced Motion Control, AMC 2018
Country/TerritoryJapan
CityTokyo
Period18/3/918/3/11

Keywords

  • Model-based predictive control
  • Networked-based control
  • Tele-operation system
  • Time delay system

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Mechanical Engineering
  • Control and Optimization

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