基于分布种群遗传算法的PID控制器参数优化整定

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基于分布种群遗传算法的PID控制器参数优化整定

陈庆更, 王宁,

文章导航 > 自动化学报 > 2005 > 31(4): 646-650

陈庆更, 王宁, . 基于分布种群遗传算法的PID控制器参数优化整定. 自动化学报, 2005, 31(4): 646-650.

引用本文:

陈庆更, 王宁, . 基于分布种群遗传算法的PID控制器参数优化整定. 自动化学报, 2005, 31(4): 646-650.

CHEN Qing-Geng, WANG Ning, HUANG Shao-Feng. The Distribution Population-based Genetic Algorithm for Parameter Optimization PID Controller. ACTA AUTOMATICA SINICA, 2005, 31(4): 646-650.

Citation:

CHEN Qing-Geng, WANG Ning, HUANG Shao-Feng. The Distribution Population-based Genetic Algorithm for Parameter Optimization PID Controller. ACTA AUTOMATICA SINICA, 2005, 31(4): 646-650.

陈庆更, 王宁, . 基于分布种群遗传算法的PID控制器参数优化整定. 自动化学报, 2005, 31(4): 646-650.

引用本文:

陈庆更, 王宁, . 基于分布种群遗传算法的PID控制器参数优化整定. 自动化学报, 2005, 31(4): 646-650.

CHEN Qing-Geng, WANG Ning, HUANG Shao-Feng. The Distribution Population-based Genetic Algorithm for Parameter Optimization PID Controller. ACTA AUTOMATICA SINICA, 2005, 31(4): 646-650.

Citation:

CHEN Qing-Geng, WANG Ning, HUANG Shao-Feng. The Distribution Population-based Genetic Algorithm for Parameter Optimization PID Controller. ACTA AUTOMATICA SINICA, 2005, 31(4): 646-650.

基于分布种群遗传算法的PID控制器参数优化整定

陈庆更,
王宁,

1.
National Key Laboratory of Industrial Control Technology, Institute of Advanced Process, Zhejiang University, Hangzhou 310027

通讯作者:
陈庆更

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- 文章访问数: 2601
- HTML全文浏览量: 91
- PDF下载量: 1542
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出版历程
- 收稿日期: 2004-07-22
- 修回日期: 2005-02-20
- 刊出日期: 2005-07-20

The Distribution Population-based Genetic Algorithm for Parameter Optimization PID Controller

1.
National Key Laboratory of Industrial Control Technology, Institute of Advanced Process, Zhejiang University, Hangzhou 310027

More Information

Corresponding author: CHEN Qing-Geng

摘要: Enlightened by distribution of creatures in natural ecology environment, the distribution population-based genetic algorithm (DPGA) is presented in this paper. The searching capability of the algorithm is improved by competition between distribution populations to reduce the search zone. This method is applied to design of optimal parameters of PID controllers with examples, and the simulation results show that satisfactory performances are obtained.
- Distribution population /
- genetic algorithm /
- PID controller /
- parameter optimization
Abstract: Enlightened by distribution of creatures in natural ecology environment, the distribution population-based genetic algorithm (DPGA) is presented in this paper. The searching capability of the algorithm is improved by competition between distribution populations to reduce the search zone. This method is applied to design of optimal parameters of PID controllers with examples, and the simulation results show that satisfactory performances are obtained.
- Distribution population /
- genetic algorithm /
- PID controller /
- parameter optimization

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