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
收藏
页码：263 / 268
页数：6
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