《机电工程》杂志,月刊( 详细... )

中国标准连续出版物号 ISSN 1001-4551 CN 33-1088/TH
主办单位浙江省机电集团有限公司
浙江大学
主编陈 晓
副 主 编唐任仲、罗向阳(执行主编)
总 经 理罗向阳
出 版浙江《机电工程》杂志社有限公司
地 址杭州市上城区延安路95号浙江省机电集团大楼二楼211、212室
电话Tel+86-571-87041360、87239525
E-mailmeem_contribute@163.com
国外发行中国国际图书贸易总公司
订阅全国各地邮局   国外代号M3135
国内发行浙江省报刊发行局
邮发代号32-68
广告发布登记证:杭上市管广发G-001号

在线杂志

当前位置: 机电工程 >>在线杂志

一阶时滞对象的最优内模PID控制

作者:王浩坤,尚群立 日期:2008-02-25/span> 浏览:4282 查看PDF文档

一阶时滞对象的最优内模PID控制

王浩坤,尚群立
(杭州电子科技大学 自动化学院,浙江 杭州 310018)

摘要:针对使用传统PID参数整定方法难以获得最优性能的问题,介绍了一种基于内模控制的PID控制器设计方法,使用蚁群优化方法对其中的参数进行优化,使系统达到某一最优性能指标。另外介绍了一种高阶模型的降阶方法,该方法计算简单并具有较高的精度。最后同其他著名的整定方法进行了比较,结果显示该方法有较大的灵活性,在某一性能指标下可使系统获得最优或接近最优的性能。Matlab仿真研究表明了该方法是有效、可行的。
关键词:比例积分微分;内模控制;蚁群优化;模型降阶;一阶时滞对象
中图分类号:TP273文献标识码:A文章编号:1001-4551(2008)01-0014-04

An optimal PID controller design for FOPD process based on internal model control
WANG Haokun, SHANG Qunli
(College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China)
Abstract: Considering the difficulties in the tuning of PID parameters to obtain a well performance by using conventional tuning formulas, a PID parameters tuning approach based on internal model control (IMC) was proposed. In order to obtain an optimal performance, ant colony optimization (ACO) method was used to optimize the parameter of the controller. In addition, a model reduction method was introduced, the method is easy to compute and have a good precision. Compare with some wellknown PID tuning formulas, it was observed that the proposed method has more flexibility and optimal performance can be obtained under special criteria. The effectiveness and feasibility of the proposed method are verified through Matlab simulation results.
Key words: proportionintegralderivative (PID); internal mode control (IMC); ant colony optimization (ACO); model reduction; FOPD
参考文献(Reference):
[1]ASTROM K J, HAGGLUND T. The future of PID control[J]. Control Engineering Practice,2001,9(11):1163-1175.
[2]GARCIA C E, PRETT D M, MORARI M. Model predictive control: theory and practice—a survey[J]. Automatic,1989,25(3):335-348.
[3]CHANG Weider. A multicrossover genetic approach to multivariable PID controllers tuning[J]. Expert Systems with Applications,2007,33(3):620-626.
[4]HO S J, SHU L S, HO S Y. Optimizing fuzzy neural networks for tuning PID controllers using an orthogonal simulated annealing algorithm OSA[J]. Fuzzy Systems,2006,14(3):421-434.
[5]VAROL H A, BINGUL Z. A New PID Tuning Technique Using Ant Algorithm[C]//Proceedings of the 2004 American Control Conference, USA:[s. n.],2004:2154-2159.
[6]谭冠政,李文斌.基于蚁群算法的智能人工腿最优PID控制器设计[J]. 中南大学学报:自然科学版, 2004,35(1):91-96.
[7]DORIGO M, BLUM C. Ant colony optimization theory: a survey[J]. Theoretical Computer Science,2005,344(2-3):243-278.
[8]DORIGO M, BIRATTARI M, STUTZLE T. Ant colony optimization[J]. Computational Intelligence Magazine, 2006,1(4):28-39.
[9]DORIGO M, STUTZLE T. 蚁群优化[M]. 北京:清华大学出版社, 2007:250-263.
[10]HO W K, LEE T H, HAN H P. Selftuning IMCPID control with interval gain and phase margins assignment[J]. Control Systems Technology,2001,9(3):535-541.
[11]TAN Wen, LIU Jizhen, CHEN Tongwen. Comparison of some wellknown PID tuning formulas[J]. Computers and Chemical Engineering,2006,30(9):1416-1423.
[12]WANG Qingguo, LEE Tongheng, FUNG Howang. PID tuning for improved performance[J]. Control Systems Technology,1999,4(7):457-465.



友情链接

浙江机械信息网