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

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

School of Engineering

Research output: Contribution to journal › Article › peer-review

5 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 language	English
Pages (from-to)	3431-3438
Number of pages	8
Journal	International Journal of Innovative Computing, Information and Control
Volume	5
Issue number	10
Publication status	Published - Oct 1 2009

Keywords

Computational savings
Generalized predictive control
Self-tuning control

ASJC Scopus subject areas

Software
Theoretical Computer Science
Information Systems
Computational Theory and Mathematics

Cite this

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AB - 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

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

Abstract

Keywords

ASJC Scopus subject areas

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