|本期目录/Table of Contents|

[1]王 璇,史乐珍.基于改进自适应DE算法的分数阶PIλDμ参数优化[J].工业仪表与自动化装置,2017,(06):116-119.[doi:1000-0682（2017）06-0116-04]
　WANG Xuan,SHI Lezhen.Fractional order PIλDμ parameters optimization based on improved adaptive DE algorithm[J].Industrial Instrumentation & Automation,2017,(06):116-119.[doi:1000-0682（2017）06-0116-04]
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基于改进自适应DE算法的分数阶PIλDμ参数优化

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2017年06期
页码:
116-119
栏目:
出版日期:
2017-12-15

文章信息/Info

Title:
Fractional order PIλDμ parameters optimization based on improved adaptive DE algorithm
作者:
王 璇; 史乐珍
南京工业大学 机械与动力工程学院，南京 211816
Author(s):
WANG Xuan;  SHI Lezhen
College of Mechanical and Power Engineering，Nanjing Tech University，Nanjing 211816，China
关键词:
差分进化算法; 自适应; 分数阶PIλDμ; 参数优化
Keywords:
differential evolution algorithm;  self-adaptation;  fractional order PIλDμ;  parameter optimization
分类号:
TP273
DOI:
1000-0682（2017）06-0116-04
文献标志码:
A
摘要:
通过实现变异算子F和交叉算子CR的自适应，改进差分进化算法。将改进后的算法用于优化直流电机位置伺服系统的分数阶PIλDμ控制器参数，并评价其位置阶跃响应性能。实验结果表明，对于分数阶PIλDμ参数的整定，相较于粒子群算法、遗传算法、传统差分进化算法而言，用改进差分进化算法优化后的控制系统具有响应速度快、超调量小等优点。
Abstract:
By realizing the adaptive of the mutation operator F and crossover operator CR, the improved differential evolution algorithm is proposed.The improved algorithm is used to optimize the fractional order PIλDμ controller parameters of the DC motor position servo system and evaluate its position step response performance. The experimental results show that for the fractional order PIλDμ parameter tuning, compared with the particle swarm optimization algorithm, the genetic algorithm and the traditional differential evolution algorithm,the optimized control system with improved differential evolution algorithm has fast response speed and small overshoot.

参考文献/References:

[1] 高建龙.分数阶PID控制器在伺服系统中的应用及实现[D].南京理工大学,2013. [2] 李大字,刘展,靳其兵,等.基于遗传算法的分数阶控制器参数整定研究[C].中国过程控制会议,2006:384-387. [3] Supol Kansit,Wudhichai Assawinchaichote. Optimization of PID Controller Based on PSOGSA for an Automatic Voltage Regulator System[J].Procedia Computer Science, 2016,86: [4] Yu Yuzhen, Ren Xinyi, Deng Chunyan,et al. Regulation of PID Controller Parameters Based on Ant Colony Optimization Algorithm in Bending Control System[J]. Applied Mechanics and Materials,2012,1500(128): [5] Gilberto Reynoso-Meza, Javier Sanchis, Juan M Herrero, et al. Evolutionary auto-tuning algorithm for PID controllers[J]. IFAC Proceedings Volumes,2012,45(3): [6] Storn R, Price K. Differential Evolution–A Simple and Efficient Heuristic for global Optimization over Continuous Spaces[J].Journal of Global Optimization, 1997, 11(4):341-359. [7] 徐斌.基于差分进化算法的多目标优化方法研究及其应用[D].华东理工大学,2013. [8] Scherer R, Kalla S L, Tang Y, et al. The Grunwald- Letnikov method for fractional differential equations[J]. Computers & Mathematics with Applications, 2011, 62(3): 902-917. [9] Xue D, Zhao C, Chen Y Q. A Modified Approximation Method of Fractional Order System[C]//IEEE International Conference on Mechatronics and Automation, 2006: 1043-1048. [10] 李创,王景成.基于改进差分进化的分数阶PIλDμ参数整定[J].控制工程, 2010, 17(4):101-105. [11] Abraham A, Biswas A, Das S, et al. Design of fractional order PIλDμ, controllers with an improved differential evolution[C]//Conference on Genetic and Evolutionary Computation,ACM, 2008:1445-1452. [12] 周晓亮.改进差分进化算法在分数阶控制系统中的应用[D].哈尔滨工程大学,2013. [13] Shahri M E, Balochian S, Balochian H, et al. Design of fractional-order PID controllers for time delay systems using differential evolution algorithm[J]. Indian Journal of Science & Technology, 2014, 7(9):1307-1315.

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备注/Memo

备注/Memo:
收稿日期：2017-03-27 作者简介：王璇（1995），女，江苏淮安人，本科，研究方向为智能控制算法。
更新日期/Last Update: 2017-12-01