Two Degree-of-Freedom of Self-Tuning Generalized Predictive Control Based on State Space Approach Using a Genetic Algorithm

被引：0
|
作者：
Yanou, Akira [1 ]
机构：
[1] Kinki Univ, Sch Engn, Higashihiroshima 7392116, Japan
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL, VOLS 1 AND 2 | 2009年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Generalized Predictive Control (GPC) achieves a robust tracking for step-type reference signal by including an integrator in advance. Although author has proposed a design scheme of two degree-of-freedom GPC system which reveals an effect of integral compensation only if there exists modeling error or disturbance, a gain for integral compensation must be selected by trial and error. In this paper, a new scheme of two degree-of-freedom of self-tuning GPC system is obtained by using a genetic algorithm for selection of integral gain.
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页码：404 / 409
页数：6
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