MULTIOBJECTIVE TUNING OF ROBUST GPC CONTROLLERS USING EVOLUTIONARY ALGORITHMS

被引：0

作者：

Herrero, J. M. ^{[1
]}

Blasco, X. ^{[1
]}

Martinez, M. ^{[1
]}

Sanchis, J. ^{[1
]}

机构：

[1] Univ Politecn Valencia, Inst Univ Automat & Informat Ind, Valencia 46022, Spain

来源：

IJCCI 2009: PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL INTELLIGENCE | 2009年

关键词：

Multiobjective optimization; Evolutionary algorithms; Predictive control; GENERALIZED PREDICTIVE CONTROL; IDENTIFICATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this article a procedure to tune robust Generalized Predictive Controllers (GPC) is presented. To tune the controller parameters a multiobjective optimization problem is formulated so the designer can consider conflicting objectives simultaneously without establishing any prior preference. Moreover model uncertainty, represented by a list of possible models, is considered. The multiobjective problem is solved with a specific Evolutionary Algorithm (ev-MOGA). Finally, an application to a non-linear thermal process is presented to illustrate the technique.

引用

页码：263 / 268

页数：6

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