基于H_∞最优控制理论的粒子群优化算法在造纸定量控制中的应用
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摘要
针对造纸定量控制系统具有非线性、时滞、多干扰等控制难点,本课题提出一种基于H_∞最优控制理论的粒子群优化算法(PSO)优化PID参数。改进的PSO具有对控制系统过程模型的依赖性小、参数整定简单、鲁棒性和抗干扰性强的特点。与传统算法相比,基于H_∞最优控制理论的PSO可以高效地找出符合设计要求的PID调节参数,不会陷入局部最优,且使系统性能指标达到最优或次最优。并且,仿真结果也验证了该算法的有效性和实用性。
Basis weight control system in paper manufacturing process is a high order non-linear system with time delay and complicated interference. According to the characteristics of basis weight control system,this paper proposed a PSO-PID parameters tuning method based on H_∞ optimal control theory. By introducing the liner decreasing inertia weight ω to optimize the PSO's global and local searching ability. Simulation results verified that the proposed strategy could find a group of PID tuning parameters efficiently,thereby reducing the searching scope. Furthermore,compared to conventional PID parameter tuning methods,this strategy had a better convergence rate and computation precision; robustness and response speed of the system were improved as well.
Basis weight control system in paper manufacturing process is a high order non-linear system with time delay and complicated interference. According to the characteristics of basis weight control system,this paper proposed a PSO-PID parameters tuning method based on H_∞ optimal control theory. By introducing the liner decreasing inertia weight ω to optimize the PSO's global and local searching ability. Simulation results verified that the proposed strategy could find a group of PID tuning parameters efficiently,thereby reducing the searching scope. Furthermore,compared to conventional PID parameter tuning methods,this strategy had a better convergence rate and computation precision; robustness and response speed of the system were improved as well.
引文
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[17]OU Lin-lin,ZHANG Wei-dong,GU Dan-ying.The Robustness Analysis of First-order Systems with Time Delay under PID Control[J].Journal of Shanghai Jiao Tong University,2006(11):1.欧林林,张卫东,顾诞英.PID控制作用下一阶时滞系统的鲁棒稳定性分析[J].上海交通大学学报,2006(11):1.
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[21]CHEN Gui-min,JIA Jian-yuan,HAN Qi.Study on the Strategy of Decreasing Inertia Weight in Particle Swarm Optimization Algorithm[J].Journal of Xi'an Jiao Tong University,2006,40(1):53.陈贵敏,贾建援,韩琪.粒子群优化算法的惯性权值递减策略研究[J].西安交通大学学报,2006,40(1):53.
[22]Ni Rui-jun.Research on Improved Particle Swarm Optimization Algotithm for Power transmission network expansion planning[D].Hangzhou:Zhejiang University,2013.倪瑞君.基于改进粒子群算法的输电网扩展规划研究[D].杭州:浙江大学,2013.
[23]ZHAN Feng,WEI Xing,GUO Jian-quan,et al.PID Parameters Tuning based on Improved PSO Algorithm[J].Power System Protection and Control.2005,33(19):23.湛锋,魏星,郭建全,等.基于改进粒子群优化算法的PID参数整定[J].电力系统保护与控制,2005,33(19):23.
[2]Tan W.Unified tuning of PID load frequency controller for power systems via IMC[J].IEEE Transactions on power systems,2010,25(1):341.
[3]Alcántara S.IMC-like analytical View the Math ML source design with S/SP mixed sensitivity consideration:Utility in PID tuning guidance[J].Journal of Process Control,2011,21(6):976.
[4]ZHAO Qian-mei,CHEN Shuai-shuai,HU Mu-yi,et al.The Expertfuzzy PID Control System of Pulp Concentration[J].China Pulp&Paper,2015,34(12):53.赵倩梅,陈帅帅,胡慕伊,等.纸浆浓度的专家-模糊PID控制系统[J].中国造纸,2015,34(12):53.
[5]Zhang Wei-dong,He Xing,Xu Xiao-ming.Smith Predictor Design for Self-Regulating and Nonself-Regulating Plants[J].Acta Automatica Sinica,2000,26(4):485.张卫东,何星,许晓鸣.自衡和非自衡时滞对象Smith预估器解析设计[J].自动化学报,2000,26(4):485.
[6]ZHENG En-rang.Control on Smith Controller of Papermaking Process Water and Basis Weight[J].Control and Instruments in Chemical Industry,2002,22(3):19.郑恩让.基于Smith预估器的抄纸过程水分定量控制[J].化工自动化及仪表,2002,22(3):19.
[7]LIU Tao,HUANG Jing-tao,ZHANG Xiang-yang,et al.A Dynamic Matrix Control Algorithm with Delayed Model Prediction Error[J].Computer Simulation,2015,32(8):347.刘涛,黄景涛,张向阳,等.基于模型预测误差延迟动态矩阵控制算法[J].计算机仿真,2015,32(8):347.
[8]Song Chong-hui,Chai Tian-you.A weighted predictive Control Algorithm with Guaranteed Stability[J].Acta Automatica Sinica,2004,30(6):807.宋崇辉,柴天佑.一类具有稳定性的广义预测控制算法[J].自动化学报,2004,30(6):807.
[9]JIANG Su-ying,ZHENG En-rang.Predictive Control of Quantification and Moisture System in Paper Process[J].Computer Simulation,2015,32(10):350.姜苏英,郑恩让.抄纸过程定量水分系统的预测控制[J].计算机仿真,2015,32(10):350.
[10]Shi Feng,Wang Hui,Yu Lei,et al.30 Case Studies of Matlab Intelligent Algorithm[M].Beijing:Beihang University Press 2011.史峰,王辉,郁磊,等.MATLAB智能算法30个案例分析[M].北京:北京航空航天大学出版社,2011.
[11]Kennedy J,Eberhart R C.Particle Swarm Optimization[C].Proceedings of IEEE International Conference on Neural Networks,Perth,Australia,1995.
[12]Eberhart R C,Shi Y.Particle swarm optimization:Developments,applications and resources[C].Congr.Evol.Comput,2001(1),81.
[13]CHEN Qian-yu,CHEN Wei-rong,DAI Zhao-hua,et al.Reactive Power Optimization Based on Modified Particle Swarm Optimization Algorithm for Power System[J].Proceedings of the CSU-EPSA,2014,26(2):8.陈前宇,陈维荣,戴朝华,等.基于改进PSO算法的电力系统无功优化[J].电力系统及其自动化学报,2014,26(2):8.
[14]Wang Qing-yan,Ma Hong-zhong,Cao Sheng.Application of Multi Strategy particle swarm optimization in magnetic levitation bearing machine[J].Proceedings of the Chinese society of electrical engineering,2014,34(30):5416.王庆燕,马宏忠,曹生让.多策略粒子群算法在磁悬浮承重装置中的应用[J].中国电机工程学报,2014,34(30):5416.
[15]Yang Z,Chen Z T,Fan Z P,et al.Tuning of PID controller based on improved particle-swarm-optimization[J].Control Theory&Applications,2010,27(10):1345.杨智,陈志堂,范正平,等.基于改进粒子群优化算法的PID控制器整定[J].控制理论与应用,2010,27(10):1345.
[16]ZHANG Wei-dong.Research on Analytical Design Method of Process control[R].Shanghai:Postdoctoral Research Report of Shanghai Jiao Tong University,1998.张卫东.过程控制解析设计方法研究[R].上海:上海交通大学博士后研究工作报告,1998.
[17]OU Lin-lin,ZHANG Wei-dong,GU Dan-ying.The Robustness Analysis of First-order Systems with Time Delay under PID Control[J].Journal of Shanghai Jiao Tong University,2006(11):1.欧林林,张卫东,顾诞英.PID控制作用下一阶时滞系统的鲁棒稳定性分析[J].上海交通大学学报,2006(11):1.
[18]Zhang W D.Quantitative Process Control Theory[C].CRC Press,2011.77.
[19]Ou L,Zhang W,Gu D.Sets of Stabilising PID Controllers for Second-order Integrating Processes with Time Delay[J].IEE Proceedings-Control Theory and Applications,2006,153(5):607.
[20]Shi Y,Ebethart R C.Empirical study of Particle swarm ptimization.Evolutionary Computation,1999[C].Washington DC:IEEE Service Center,1999.
[21]CHEN Gui-min,JIA Jian-yuan,HAN Qi.Study on the Strategy of Decreasing Inertia Weight in Particle Swarm Optimization Algorithm[J].Journal of Xi'an Jiao Tong University,2006,40(1):53.陈贵敏,贾建援,韩琪.粒子群优化算法的惯性权值递减策略研究[J].西安交通大学学报,2006,40(1):53.
[22]Ni Rui-jun.Research on Improved Particle Swarm Optimization Algotithm for Power transmission network expansion planning[D].Hangzhou:Zhejiang University,2013.倪瑞君.基于改进粒子群算法的输电网扩展规划研究[D].杭州:浙江大学,2013.
[23]ZHAN Feng,WEI Xing,GUO Jian-quan,et al.PID Parameters Tuning based on Improved PSO Algorithm[J].Power System Protection and Control.2005,33(19):23.湛锋,魏星,郭建全,等.基于改进粒子群优化算法的PID参数整定[J].电力系统保护与控制,2005,33(19):23.