多变量内模控制的仿真研究
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摘要
在现实化工过程中,多变量系统广泛存在,由于存在各回路之间的加大较大耦合、多时滞等特性,而传统的单变量PID控制的方法难于保证控制精度或难以控制。本文选取典型多变量化工过程系统为研究对象,提出了基于全极点近似的时滞系统的内模PID控制,提出了两种基于v规范型解耦的多变量内模控制设计的新方法,进行了多变量内模滤波器寻优,简单研究了主控变量法和广义逆法的胖系统多变量内模控制。具体如下:
1.提出了基于全极点近似的时滞系统的内模控制,将全极点近似法引入内模控制设计,并将其应用于IMC-PID的转化过程,推导出了IMC-PID控制器参数计算的一般通式,便于仿真编程的实现,及在多变量内模控制中的直接应用。仿真结果表明,全极点近似法的近似程度高,系统的控制效果好,且仍具有很强的鲁棒性。
2.提出了两类基于v规范型解耦的多变量内模控制设计的新方法:基于v规范型的新型多变量解耦内模控制和基于v规范解耦环节的多变量内模控制。分别对其进行系统性地解耦分析,详细推导控制器设计,得到控制器设计的一般通式,得到不同类型的v规范型解耦的IMC-PID转化结构,分别形成了较为完整的控制分析和设计方法的体系。
3.将NLJ优化算法引入两种新型的多变量内模控制方法,以一种改进的综合跟踪特性与解耦特性的ITAE指标最优为目标,对滤波器参数进行寻优,仿真结果证明,控制良好,抗干扰能力强,且易于在工程中DCS的应用。
4.针对胖系统研究了两种内模控制方法:主控量法和广义逆法。仿真结果表明,控制效果良好。
本文率先进行了多变量系统的IMC-PID设计研究,并给出了可行性的方法,是一个创新。
In reality,many chemical process is a complex multivariable instability, and time-delay system,and there is greater coupling,while the traditional method of PID control can not be solved.In this paper,the all-pole similarity is proposed for the time-delay of IMC-PID system,and we study typical multi-variable systems for the chemical process study and propose two design methods which based on the v-norm decoupling of the new multi-variable IMC design and optimization.NLJ optimization algorithm has been used in this two IMC method.For fat systems,two kinds of IMC design methods have been proposed:main manipulated variable method and generalized inverse method.As follows:
1.The all-pole similarity is proposed for the time-delay of IMC-PID system,put into internal model control for the first time,applied to IMC-PID of the transformation process,and derived from the IMC-PID control parameters calculated General formula to facilitate the realization of simulation programming.The simulation results show that the entire pole approximation method similar to the high level of effective systems of control and still has strong robustness.
2.It is proposed two methods of v-norm decoupling multi-variable IMC design:multi-variable v-norm decoupling IMC design and multi-variable IMC design with v-norm decoupling system.They were carried out systematic analysis of decoupling,derived from IMC controller in detail,and calculate the general formula of controller.The different v-norm IMC-PID controller can be got.So formed a relatively complete set of analysis and control design of the system
3.NLJ optimization algorithm has been used in this two IMC method, and improves a comprehensive tracking features and decoupling of ITAE optimal as the goal for the filter parameters optimization.And put them into simulation.The results are good,which haveconfirmed these two design methods very good versatility and the optimized algorithm validity.
4.For the non-square systems,two kinds of IMC design methods have been proposed:main manipulated variable method and generalized inverse method.The simulation results show that effective control.
This article was the first multi-variable system of the IMC-PID design research,and gives the feasibility of methods,which is an innovative.
1.提出了基于全极点近似的时滞系统的内模控制,将全极点近似法引入内模控制设计,并将其应用于IMC-PID的转化过程,推导出了IMC-PID控制器参数计算的一般通式,便于仿真编程的实现,及在多变量内模控制中的直接应用。仿真结果表明,全极点近似法的近似程度高,系统的控制效果好,且仍具有很强的鲁棒性。
2.提出了两类基于v规范型解耦的多变量内模控制设计的新方法:基于v规范型的新型多变量解耦内模控制和基于v规范解耦环节的多变量内模控制。分别对其进行系统性地解耦分析,详细推导控制器设计,得到控制器设计的一般通式,得到不同类型的v规范型解耦的IMC-PID转化结构,分别形成了较为完整的控制分析和设计方法的体系。
3.将NLJ优化算法引入两种新型的多变量内模控制方法,以一种改进的综合跟踪特性与解耦特性的ITAE指标最优为目标,对滤波器参数进行寻优,仿真结果证明,控制良好,抗干扰能力强,且易于在工程中DCS的应用。
4.针对胖系统研究了两种内模控制方法:主控量法和广义逆法。仿真结果表明,控制效果良好。
本文率先进行了多变量系统的IMC-PID设计研究,并给出了可行性的方法,是一个创新。
In reality,many chemical process is a complex multivariable instability, and time-delay system,and there is greater coupling,while the traditional method of PID control can not be solved.In this paper,the all-pole similarity is proposed for the time-delay of IMC-PID system,and we study typical multi-variable systems for the chemical process study and propose two design methods which based on the v-norm decoupling of the new multi-variable IMC design and optimization.NLJ optimization algorithm has been used in this two IMC method.For fat systems,two kinds of IMC design methods have been proposed:main manipulated variable method and generalized inverse method.As follows:
1.The all-pole similarity is proposed for the time-delay of IMC-PID system,put into internal model control for the first time,applied to IMC-PID of the transformation process,and derived from the IMC-PID control parameters calculated General formula to facilitate the realization of simulation programming.The simulation results show that the entire pole approximation method similar to the high level of effective systems of control and still has strong robustness.
2.It is proposed two methods of v-norm decoupling multi-variable IMC design:multi-variable v-norm decoupling IMC design and multi-variable IMC design with v-norm decoupling system.They were carried out systematic analysis of decoupling,derived from IMC controller in detail,and calculate the general formula of controller.The different v-norm IMC-PID controller can be got.So formed a relatively complete set of analysis and control design of the system
3.NLJ optimization algorithm has been used in this two IMC method, and improves a comprehensive tracking features and decoupling of ITAE optimal as the goal for the filter parameters optimization.And put them into simulation.The results are good,which haveconfirmed these two design methods very good versatility and the optimized algorithm validity.
4.For the non-square systems,two kinds of IMC design methods have been proposed:main manipulated variable method and generalized inverse method.The simulation results show that effective control.
This article was the first multi-variable system of the IMC-PID design research,and gives the feasibility of methods,which is an innovative.
引文
[1]王树清.先进控制技术及应用[M].北京:化学工业出版社,2001.48-78
[2]王树青,金晓明,荣冈.先进控制技术及应用[J].化工自动化及仪表,1999,26(2):61-65
[3]PavelZitek,Jaroslav Hlava.Anisochronic internal model control of time-delay systems[J].Control Engineering Practice,2001(9):501-516
[4]蒋慰孙,俞金寿.过程控制工程[M].北京:烃加工出版社,1988.111-126
[5]Kaya I.IMC based automatic tuning method for PID controllers in a Smith predictor configuration[J].Computers & Chemical Engineering,2004,28:281-290
[6]Yi Cui.Application of internal model control algorithm to pH process[D].USA:University of Nevada Reno,2002
[7]王文新,潘立登.LMC-PID鲁棒控制器设计及其在蒸馏装置上的应用[J].北京化工大学学报,2004,31(5):93-96
[8]胡国龙,孙优贤.预测控制进展及其应用研究[J].电力系统及其自动化学报,2003,15(1):109-114
[9]Stephanopoulos G,Huang H P.The 2-port control system[J].Chemical Engineering Science,1986,41(6):1161-1630
[10]周涌,陈庆伟,胡维礼.内模控制研究的新发展[J].控制理论与应用,2004,21(3):475-479
[11]Garcia,C.E,Morari,M.Internal model control.A Unifying Review and Some New results [J].Int.Eng.Chem.Process Des.Dev.,1982(21):308-323
[12]Garcia,C.E,Morari,M.Internal model control.Design procedure for multivariable systems[J].Industrial Engineering Chemistry Process Design and Development,1985(24):472-484.
[13]ZAFIRIOU E,Morari,M.Internal model control:robust digital controller synthesis for multivariable open- loop stable or unstable processes[J].Int J Control,1991(54):665-704.
[14]Morari,M,ZAFIRIOUS E.Robust Process Control[M].New Jersey,Prentice-Hall,1989
[15]ECONOMOU C G.Internal model control-5:extension to nonlinear systems[J].Industrial Engineering Chemistry Process Design and Development,1986(25):403-411.
[16]HUNT K J,SBURBURO D.Neural networks for nonlinear internal model control[J].IEE Proc-D,1991(13):431-438.
[17]NAHAS E P.Nonlinear internal model control strategy for neural network models[J].Computers Chemical Engineering,1992(16):1039-1057.
[18]樊卫华.高性能交流数字伺服系统的算法研究与工程实现[D].南京:南京理工大学,2001
[19]刘开培.基于Pade逼近的纯滞后系统增益自适应内模PID控制[J].武汉大学学报(工学版),2001(34):93-95
[20]陈娟,闫聪,潘立登,等.基于遗传算法时滞系统的滤波器参数自调整内模控制[J].北京交通大学学报.2005(29):47-51
[21]Qiuping Hu,Gade Pandu Rangaiah.Adaptive internal model control of nonlinear processes[J].Chemical Engineering Science,1999(54),1205-1220
[22]金秀章,刘吉臻,牛玉广,等.自适应内模控制在主蒸汽温度控制系统中的应用研究 [J].中国电机工程学报,2003(23):225-229
[23]郑恩让,张玲.内模控制在造纸生产定量控制中的应用[J].化工自动化及仪表,2001(28):23-24
[24]ZHOU Lifang,QIAN Jixin.The IMC Structure of Multi-rate Multivafiable Predictive Control Systems and an Improved Algorithm[J].Chinese J.of Chem.Eng,2001(9):273-279
[25]ERIC COULIBALY,SANDIP MAITI,COLEMAN BROSILOW.Internal Model Predictive Control(IMPC)[J].Automatica,1995(31):1471-1482
[26]汪宁,严德昆.多变量系统CARMA模型近似解耦法[J].工业仪表与自动化装置,2002:11-13
[27]陈平,潘立登.一类非线性多变量对象的解耦内模控制[J].控制工程,2005(12):14-17
[28]Wen Tan,Horacio J.Marquez,Tongwen Chen.IMC design for unstable processes with time delays[J].Journal of Process Control,2003(13):203-213
[29]TAYEBI A,ZAREMBA M B.Internal model-based robust iterative learning control for uncertain LTI systems[C].Proc of IEEE Conf on Decision and Control.Sydney:IEEE Press,2000(4):3439-3444.
[30]张井岗,李临生,陈志梅,等.二自由度PID调节器的内模整定方法[J].仪器仪表学报,2002,23(1):28-30
[31]TSYPKIN Y Z,HOLMBERG U.Robust stochastic control using internal model principle and internal model control[J].Int J Control,1995,61(4):809-822
[32]王文新,潘立登,IMC-PID鲁棒控制器设计及其在蒸馏装置上的应用[J].北京化工大学学报,2004,31(5):93-96
[33]Morari.M.Skogestad.S.,Rivera.D.E.Implications of Internal Model Control for PID Controllers[A].In:Proc.of American Control Conference,San Diego,CA,1984:661-666
[34]Lideng Pan,Wenxin Wang,NingchuanWu.The Design of Robust IMC-PID Controller and its Application to Atmospheric and Vacuum Distillation Unit[A].The 6th World Multiconference on Systemics,Cybernetics and Informatics,July 14-18,2002,Orlando,Florida,USA,Proceedings,Volume Ⅵ,Industrial Systems and Engineering:353-358
[35]Guan Tien Tan,Min-Sen Chiu.A multiple-model approach to decentralized internal model control design[J].Chemical Engineering Science,2001(56):6651-6660
[36]薛美盛,吴刚,孙德敏,等.工业过程的先进控制[J].化工自动化及仪表,2002,29(2):1-9
[37]ECONOMOU C G.,Internal model control-5:extension to nonlinear systems[J],Industrial Chemistry Process Design and Development,1986,25930:403-411
[38]孙鑫,孔亚广,孙优贤.造纸过程定量水分的建模与控制[J].应用力学学报,2000(5):19-23
[39]郑思让,张玲.内模控制在造纸生产定量控制中的应用[J].应用力学学报,2001,28(3):23-24
[40]陈志辉,严仰光.IMC控制在双凸极发电机电压调节中的应用[J].电工技术杂志,2000(6):28-29
[41]张建华,侯国莲,李农庄,等.基于内模控制的再热汽温控制系统[J].现代电力,1999,16(1):5-10
[42]许天舒,史小平.核电站反应堆冷却剂平均温度内模控制系统仿真[J].哈尔滨理工大学学报,2001,26(2):26-30
[43]赵曜.直流调速系统2自由度内模控制与PID控制的比较[A].中国控制会议论文集,武汉出版社,1997:1109-1112
[44]游浩.内模控制和IMC-PID控制及其应用[D].北京:北京化工大学,2000
[45]龚晓峰,高衿畅,周春晖.时滞系统PID控制器内模整定方法的扩展[J].控制与决策,1998,13(4):337-341
[46]王诗宓.多变量控制系统的分析和设计[M].北京:中国电力出版社,1996.219-436
[47]刘晨晖.多变量过程控制系统解耦理论[M].北京:水利电力出版社,1984.19-231
[48]李全善,潘立登,王文新,等.催化裂化装置PID控制回路的优化[J].石油炼制与化工,2004,35(9):46-50
[49]刘慧,袁文燕,姜冬青.矩阵论及应用[M].北京:化学工业出版社,2003.187-189
[50]王全良.基于DCS的多变量内模控制及其应用研究[D].北京:北京化工大学,2005
[2]王树青,金晓明,荣冈.先进控制技术及应用[J].化工自动化及仪表,1999,26(2):61-65
[3]PavelZitek,Jaroslav Hlava.Anisochronic internal model control of time-delay systems[J].Control Engineering Practice,2001(9):501-516
[4]蒋慰孙,俞金寿.过程控制工程[M].北京:烃加工出版社,1988.111-126
[5]Kaya I.IMC based automatic tuning method for PID controllers in a Smith predictor configuration[J].Computers & Chemical Engineering,2004,28:281-290
[6]Yi Cui.Application of internal model control algorithm to pH process[D].USA:University of Nevada Reno,2002
[7]王文新,潘立登.LMC-PID鲁棒控制器设计及其在蒸馏装置上的应用[J].北京化工大学学报,2004,31(5):93-96
[8]胡国龙,孙优贤.预测控制进展及其应用研究[J].电力系统及其自动化学报,2003,15(1):109-114
[9]Stephanopoulos G,Huang H P.The 2-port control system[J].Chemical Engineering Science,1986,41(6):1161-1630
[10]周涌,陈庆伟,胡维礼.内模控制研究的新发展[J].控制理论与应用,2004,21(3):475-479
[11]Garcia,C.E,Morari,M.Internal model control.A Unifying Review and Some New results [J].Int.Eng.Chem.Process Des.Dev.,1982(21):308-323
[12]Garcia,C.E,Morari,M.Internal model control.Design procedure for multivariable systems[J].Industrial Engineering Chemistry Process Design and Development,1985(24):472-484.
[13]ZAFIRIOU E,Morari,M.Internal model control:robust digital controller synthesis for multivariable open- loop stable or unstable processes[J].Int J Control,1991(54):665-704.
[14]Morari,M,ZAFIRIOUS E.Robust Process Control[M].New Jersey,Prentice-Hall,1989
[15]ECONOMOU C G.Internal model control-5:extension to nonlinear systems[J].Industrial Engineering Chemistry Process Design and Development,1986(25):403-411.
[16]HUNT K J,SBURBURO D.Neural networks for nonlinear internal model control[J].IEE Proc-D,1991(13):431-438.
[17]NAHAS E P.Nonlinear internal model control strategy for neural network models[J].Computers Chemical Engineering,1992(16):1039-1057.
[18]樊卫华.高性能交流数字伺服系统的算法研究与工程实现[D].南京:南京理工大学,2001
[19]刘开培.基于Pade逼近的纯滞后系统增益自适应内模PID控制[J].武汉大学学报(工学版),2001(34):93-95
[20]陈娟,闫聪,潘立登,等.基于遗传算法时滞系统的滤波器参数自调整内模控制[J].北京交通大学学报.2005(29):47-51
[21]Qiuping Hu,Gade Pandu Rangaiah.Adaptive internal model control of nonlinear processes[J].Chemical Engineering Science,1999(54),1205-1220
[22]金秀章,刘吉臻,牛玉广,等.自适应内模控制在主蒸汽温度控制系统中的应用研究 [J].中国电机工程学报,2003(23):225-229
[23]郑恩让,张玲.内模控制在造纸生产定量控制中的应用[J].化工自动化及仪表,2001(28):23-24
[24]ZHOU Lifang,QIAN Jixin.The IMC Structure of Multi-rate Multivafiable Predictive Control Systems and an Improved Algorithm[J].Chinese J.of Chem.Eng,2001(9):273-279
[25]ERIC COULIBALY,SANDIP MAITI,COLEMAN BROSILOW.Internal Model Predictive Control(IMPC)[J].Automatica,1995(31):1471-1482
[26]汪宁,严德昆.多变量系统CARMA模型近似解耦法[J].工业仪表与自动化装置,2002:11-13
[27]陈平,潘立登.一类非线性多变量对象的解耦内模控制[J].控制工程,2005(12):14-17
[28]Wen Tan,Horacio J.Marquez,Tongwen Chen.IMC design for unstable processes with time delays[J].Journal of Process Control,2003(13):203-213
[29]TAYEBI A,ZAREMBA M B.Internal model-based robust iterative learning control for uncertain LTI systems[C].Proc of IEEE Conf on Decision and Control.Sydney:IEEE Press,2000(4):3439-3444.
[30]张井岗,李临生,陈志梅,等.二自由度PID调节器的内模整定方法[J].仪器仪表学报,2002,23(1):28-30
[31]TSYPKIN Y Z,HOLMBERG U.Robust stochastic control using internal model principle and internal model control[J].Int J Control,1995,61(4):809-822
[32]王文新,潘立登,IMC-PID鲁棒控制器设计及其在蒸馏装置上的应用[J].北京化工大学学报,2004,31(5):93-96
[33]Morari.M.Skogestad.S.,Rivera.D.E.Implications of Internal Model Control for PID Controllers[A].In:Proc.of American Control Conference,San Diego,CA,1984:661-666
[34]Lideng Pan,Wenxin Wang,NingchuanWu.The Design of Robust IMC-PID Controller and its Application to Atmospheric and Vacuum Distillation Unit[A].The 6th World Multiconference on Systemics,Cybernetics and Informatics,July 14-18,2002,Orlando,Florida,USA,Proceedings,Volume Ⅵ,Industrial Systems and Engineering:353-358
[35]Guan Tien Tan,Min-Sen Chiu.A multiple-model approach to decentralized internal model control design[J].Chemical Engineering Science,2001(56):6651-6660
[36]薛美盛,吴刚,孙德敏,等.工业过程的先进控制[J].化工自动化及仪表,2002,29(2):1-9
[37]ECONOMOU C G.,Internal model control-5:extension to nonlinear systems[J],Industrial Chemistry Process Design and Development,1986,25930:403-411
[38]孙鑫,孔亚广,孙优贤.造纸过程定量水分的建模与控制[J].应用力学学报,2000(5):19-23
[39]郑思让,张玲.内模控制在造纸生产定量控制中的应用[J].应用力学学报,2001,28(3):23-24
[40]陈志辉,严仰光.IMC控制在双凸极发电机电压调节中的应用[J].电工技术杂志,2000(6):28-29
[41]张建华,侯国莲,李农庄,等.基于内模控制的再热汽温控制系统[J].现代电力,1999,16(1):5-10
[42]许天舒,史小平.核电站反应堆冷却剂平均温度内模控制系统仿真[J].哈尔滨理工大学学报,2001,26(2):26-30
[43]赵曜.直流调速系统2自由度内模控制与PID控制的比较[A].中国控制会议论文集,武汉出版社,1997:1109-1112
[44]游浩.内模控制和IMC-PID控制及其应用[D].北京:北京化工大学,2000
[45]龚晓峰,高衿畅,周春晖.时滞系统PID控制器内模整定方法的扩展[J].控制与决策,1998,13(4):337-341
[46]王诗宓.多变量控制系统的分析和设计[M].北京:中国电力出版社,1996.219-436
[47]刘晨晖.多变量过程控制系统解耦理论[M].北京:水利电力出版社,1984.19-231
[48]李全善,潘立登,王文新,等.催化裂化装置PID控制回路的优化[J].石油炼制与化工,2004,35(9):46-50
[49]刘慧,袁文燕,姜冬青.矩阵论及应用[M].北京:化学工业出版社,2003.187-189
[50]王全良.基于DCS的多变量内模控制及其应用研究[D].北京:北京化工大学,2005