An extension of self-tuning two degree-of-freedom GPC based on polynomial approach with computational savings

Akira Yanou, Shiro Masuda, Mingcong Deng, Akira Inoue

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

This paper extends a self-tuning two degree-of-freedom generalized predictive control(GPC) by using Youla-Kucera parametrization and saves the amount of computation to calculate the controller by reducing the number of solving Diophantine equation. The proposed method reveals the effect of the integral compensation only if there is modeling error or disturbance in the case that the identified plant parameters converge on true values. And it aims for easier application of the self-tuning GPC to practical systems by computational savings. ICIC International

Original languageEnglish
Pages (from-to)3431-3438
Number of pages8
JournalInternational Journal of Innovative Computing, Information and Control
Volume5
Issue number10
Publication statusPublished - Oct 2009

Fingerprint

Generalized Predictive Control
Self-tuning
Tuning
Degree of freedom
Polynomials
Polynomial
Modeling Error
Diophantine equation
Parametrization
Disturbance
Converge
Controller
Calculate
Controllers
Compensation and Redress

Keywords

  • Computational savings
  • Generalized predictive control
  • Self-tuning control

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Information Systems
  • Software
  • Theoretical Computer Science

Cite this

An extension of self-tuning two degree-of-freedom GPC based on polynomial approach with computational savings. / Yanou, Akira; Masuda, Shiro; Deng, Mingcong; Inoue, Akira.

In: International Journal of Innovative Computing, Information and Control, Vol. 5, No. 10, 10.2009, p. 3431-3438.

Research output: Contribution to journalArticle

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