Computational intelligence approach to PID controller design using the universal model

被引：28

作者：

Sumar, Rodrigo Rodrigues ^{[2
]}

Rodrigues Coelho, Antonio Augusto ^{[3
]}

Coelho, Leandro dos Santos ^{[1
]}

机构：

[1] Pontificia Catholic Univ Parana PUCPR, Ind & Syst Engn Grad Program PPGEPS, BR-80215901 Curitiba, Parana, Brazil

[2] Fed Univ Technol UTFPR, BR-86300000 Cornellio Procopio, PR, Brazil

[3] Univ Fed Santa Catarina, Dept Automat & Syst, BR-88040900 Florianopolis, SC, Brazil

来源：

INFORMATION SCIENCES | 2010年 / 180卷 / 20期

关键词：

PID control; Nonlinear systems; Fuzzy systems; Neural networks; Differential evolution; Optimization; FUZZY CONTROL; DIFFERENTIAL EVOLUTION; NEURAL-NETWORKS; OPTIMIZATION; ALGORITHM; SYSTEMS; PLANTS;

D O I：

10.1016/j.ins.2010.06.026

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Despite the popularity of PID (Proportional-Integral-Derivative) controllers, their tuning aspect continues to present challenges for researches and plant operators. Various control design methodologies have been proposed in the literature, such as auto-tuning, self-tuning, and pattern recognition. The main drawback of these methodologies in the industrial environment is the number of tuning parameters to be selected. In this paper, the design of a PID controller, based on the universal model of the plant, is derived, in which there is only one parameter to be tuned. This is an attractive feature from the viewpoint of plant operators. Fuzzy and neural approaches - bio-inspired methods in the field of computational intelligence - are used to design and assess the efficiency of the PID controller design based on differential evolution optimization in nonlinear plants. The numerical results presented herein indicate that the proposed bio-inspired design is effective for the nonlinear control of nonlinear plants. (C) 2010 Elsevier Inc. All rights reserved.

引用

页码：3980 / 3991

页数：12

共 58 条

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