一种改进人工蜂群的分数阶PID控制器优化算法
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摘要
针对分数阶PID控制器参数整定过程参数多复杂性大,传统靠经验试凑的方法不易实现且优化效果差的问题,提出了一种改进的人工蜂群算法,实现分数阶PID控制器参数的整定;该算法通过改进人工蜂群算法中搜索方程,并引入一个淘汰机制,对分数阶控制器参数进行群智能搜索,将搜索到的参数送至分数阶PID控制器中反复迭代,以带有权值的误差绝对值积分指标(AIE)作为人工蜂群寻优的目标函数,最后得出控制器;本文以非线性系统为被控对象,经过实例仿真,验证了该算法实现的控制器比传统整数阶控制器和未改进的人工蜂群算法实现的分数阶控制器的动态性能和稳态性能都有所提高,在超调、上升时间、振荡性方面都优于未改进算法。
It is complicated to set parameters of fractional order PID controller,the optimization results from traditional method are not only difficult to achieve but poor,so this paper put forward an improved artificial colony algorithm to complete the fractional order PID controller's parameter setting.First,improving the searching equation and adding an elimination mechanism in artificial colony algorithm to achieve parameters' intelligent searching.Next those parameters will be sent to the fractional order PID controller and then repeat forementioned process.Meanwhile,using the integral of absolute error index(AIE)with weights as the objective function.Finally the controller can be concluded.This paper used a nonlinear system as a controlled object,by simulation and analysis,proved the controller'performance of improved algorithm is more better in dynamic and steady-state than the controller of traditional integer order and the controller without improved artificial colony algorithm.In addition,this new algorithm we proposed is better than not improved algorithm in the aspect of maximum overshoot,rise time and oscillation.
It is complicated to set parameters of fractional order PID controller,the optimization results from traditional method are not only difficult to achieve but poor,so this paper put forward an improved artificial colony algorithm to complete the fractional order PID controller's parameter setting.First,improving the searching equation and adding an elimination mechanism in artificial colony algorithm to achieve parameters' intelligent searching.Next those parameters will be sent to the fractional order PID controller and then repeat forementioned process.Meanwhile,using the integral of absolute error index(AIE)with weights as the objective function.Finally the controller can be concluded.This paper used a nonlinear system as a controlled object,by simulation and analysis,proved the controller'performance of improved algorithm is more better in dynamic and steady-state than the controller of traditional integer order and the controller without improved artificial colony algorithm.In addition,this new algorithm we proposed is better than not improved algorithm in the aspect of maximum overshoot,rise time and oscillation.
引文
[1]赵春娜,李英顺,陆涛.分数阶系统与设计[M].北京:国防工业出版社,2010.
[2]薛定宇,赵春娜.分数阶系统的分数阶控制器PID控制器设计[J].控制理论与应用,2007,25(5):771-776.
[3]胡建兵,赵灵东.分数阶系统稳定性理论与控制研究[J].物理学报,2013,62(24):1-7.
[4]Alain Oustaloup,Francois Levron,Benoit Mathieu M.Nanot etc.Frequency-Band Complex Noninteger Differentiatior:Characterization and Synthesis[J].Fundmental Theory and Applications,2000,7(1):25-39.
[5]Xue Dingyu.Computer Aided Control Systems Design.Using MATLAB Language[M].北京:清华大学出版社,2012.
[6]王强,赵志成,桑博.基于改进粒子群算法的分数阶系统辨识方法[J].太原科技大学学报,2014,35(3):203-206.
[7]李文,刘洋.基于遗传算法的分数阶控制器参数分级整定[J].大连交通大学学报,2009,30(6):83-85.
[8]余胜威.MATLAB优化算法案例分析与应用(进阶篇)[M].北京:清华大学出版社,2015.
[9]毕晓君,万艳娇.改进人工蜂群算法[J].哈尔滨工程大学学报,2012,33(1):118-123.
[10]李荣雨,朱正方.改进人工蜂群算法在MFAC参数整定中的研究[J].自动化仪表,2016,37(8):75-79.
[11]陈超波,胡莉,马颖,等.一种改进式遗传算法优化分数阶PID控制器[J].西安工业大学学报,2016,36(6):511-516.
[12]Li M D,Xiong W,Liang Q.Wireless Sensor Networkds Node Localization Algorithm Based on Improved ABC Algorithm[J].Acta Automatica Sinica,2014,5(5):974-980.
[13]黄丽莲,周晓亮,项建弘.分数阶PID控制器参数的自适应设计[J].系统工程与电子技术,2013,25(5):1065-1069.
[14]刘金琨.先进PID控制MATLAB仿真(第三版)[M].北京:电子工业出版社,2011.
[15]张小凤,王孝洪,田联房,等.基于分数阶PIλ控制器的有源电力滤波器直流侧电压控制[J].电力系统自动化,2013,37(16):108-113.
[16]谢伟,游敏,周玉钦.基于自适应分数阶微分的引导滤波及其应用[J].计算机应用研究,2016,34(2):1-7.
[17]尹进田,李白雅,黄海.基于DSP的模糊自适应PID伺服电机控制系统[J].电机与控制应用,2007,34(10):8-10.
[18]姚舜才,潘宏侠.粒子群优化同步电机分数阶鲁棒励磁控制器[J].控制与决策,2009,24(2):162-167.
[2]薛定宇,赵春娜.分数阶系统的分数阶控制器PID控制器设计[J].控制理论与应用,2007,25(5):771-776.
[3]胡建兵,赵灵东.分数阶系统稳定性理论与控制研究[J].物理学报,2013,62(24):1-7.
[4]Alain Oustaloup,Francois Levron,Benoit Mathieu M.Nanot etc.Frequency-Band Complex Noninteger Differentiatior:Characterization and Synthesis[J].Fundmental Theory and Applications,2000,7(1):25-39.
[5]Xue Dingyu.Computer Aided Control Systems Design.Using MATLAB Language[M].北京:清华大学出版社,2012.
[6]王强,赵志成,桑博.基于改进粒子群算法的分数阶系统辨识方法[J].太原科技大学学报,2014,35(3):203-206.
[7]李文,刘洋.基于遗传算法的分数阶控制器参数分级整定[J].大连交通大学学报,2009,30(6):83-85.
[8]余胜威.MATLAB优化算法案例分析与应用(进阶篇)[M].北京:清华大学出版社,2015.
[9]毕晓君,万艳娇.改进人工蜂群算法[J].哈尔滨工程大学学报,2012,33(1):118-123.
[10]李荣雨,朱正方.改进人工蜂群算法在MFAC参数整定中的研究[J].自动化仪表,2016,37(8):75-79.
[11]陈超波,胡莉,马颖,等.一种改进式遗传算法优化分数阶PID控制器[J].西安工业大学学报,2016,36(6):511-516.
[12]Li M D,Xiong W,Liang Q.Wireless Sensor Networkds Node Localization Algorithm Based on Improved ABC Algorithm[J].Acta Automatica Sinica,2014,5(5):974-980.
[13]黄丽莲,周晓亮,项建弘.分数阶PID控制器参数的自适应设计[J].系统工程与电子技术,2013,25(5):1065-1069.
[14]刘金琨.先进PID控制MATLAB仿真(第三版)[M].北京:电子工业出版社,2011.
[15]张小凤,王孝洪,田联房,等.基于分数阶PIλ控制器的有源电力滤波器直流侧电压控制[J].电力系统自动化,2013,37(16):108-113.
[16]谢伟,游敏,周玉钦.基于自适应分数阶微分的引导滤波及其应用[J].计算机应用研究,2016,34(2):1-7.
[17]尹进田,李白雅,黄海.基于DSP的模糊自适应PID伺服电机控制系统[J].电机与控制应用,2007,34(10):8-10.
[18]姚舜才,潘宏侠.粒子群优化同步电机分数阶鲁棒励磁控制器[J].控制与决策,2009,24(2):162-167.