球磨机制粉系统分级预测模糊控制的研究与应用
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摘要
火力发电厂球磨机制粉系统是一个多变量的对象，各个变量之间不仅存在着严重的耦合，而且一些变量还存在着很大的纯迟延及时变性。对球磨机制粉系统采用经典的PID控制，很难得到较好的控制效果。所以，长期以来对球磨机制粉系统一直采用人工手动控制。如何有效的实现球磨机制粉系统的自动控制，提高自动控制的水平及制粉效率，减小工人的劳动强度，是一个亟待解决的问题。本文从模糊控制的角度对球磨机制粉系统的控制进行了深入的研究。
本文以盘县发电厂200MW机组的球磨机制粉系统的控制为研究对象，针对球磨机具有的纯滞后、大惯性和非线性、数学模型难以建立且随时间缓慢变化等特点，常规控制方法难以取得良好的控制效果。而模糊控制策略大多应用于受控对象数学模型难以建立的场合，具有较好的稳定性和鲁棒性，为此提出了按负荷、出口温度、入口负压顺序分级预测的模糊控制模型，并分析了该模型的解耦特性，同时，按该模型设计了一种模糊控制系统。采用分级模糊控制算法的目的是因为分级控制能够显著的减少模糊控制算法的规则数，此分级模糊控制算法不仅简化了多变量系统的模糊控制设计，而且还有效的解决了系统变量之间的耦合问题。提高了球磨机制粉系统模糊控制算法的自适应能力。本文对分级模糊控制在盘县电厂200MW机组I/A Series DCS集散控制系统中的应用进行了分析和研究，设计了分级模糊控制器在I/A Series DCS上的挂接方案和通讯方案，并通过对控制功能的分析能够得到良好的控制效果，能够提高制粉系统运行的经济性和安全性，有着良好的工程应用前景和价值。
The ball mill pulverizing system is a MIMO system with strong coupling, long time delay and time changing apparently. With traditional PID control system, the controlling result is not so satisfying. Thus, manual control system has been put into use for a long time. However it is still an urgent problem to be solved that how to realize the automatic control of the steel ball mill pulverizing system, how to raise the level of automation and the efficiency of the system, and how to reduce the workers' labor intensity. This paper gives a thorough research work on the control of the steel ball mill pulverizing system from the angle of the intellectual control.
The control of the ball mill pulverizing system in the 200MW unit in PanXian power plant is researched in this paper. Fuzzy control police most has application in the situation that it is difficult to establish object model. It has better stability and robustness. In allusion to the characteristic of ball mill that it is simple lag, serious inertia and nonlinear, and general control methods are hard to gain a good control impact, so a fuzzy control model is held up which is graded according to burthen, temperature of outlet, negative pressure of entry, and the coupling characteristic of the model is analyzed. Finally a fuzzy control system is designed as the model. This theory can remarkable reduce the rule number of the fuzzy control algorithm. It can not only simplify the design for multi-variables system's fuzzy control, but also solve effectively the coupling problem between variables in the system, To raise the method' self-adaptability. And these papers analyze and study the method's application in the
I/A Series DCS control system in PanXian power plants. Devised coupling precepts and communicate precepts about graded fuzzy controller in the I/A Series DCS. It can gain favorable control effect by annalyzing control function and improve the economy and security of the pulverizing system. It has a favorable engineering applied foreground and value.
本文以盘县发电厂200MW机组的球磨机制粉系统的控制为研究对象，针对球磨机具有的纯滞后、大惯性和非线性、数学模型难以建立且随时间缓慢变化等特点，常规控制方法难以取得良好的控制效果。而模糊控制策略大多应用于受控对象数学模型难以建立的场合，具有较好的稳定性和鲁棒性，为此提出了按负荷、出口温度、入口负压顺序分级预测的模糊控制模型，并分析了该模型的解耦特性，同时，按该模型设计了一种模糊控制系统。采用分级模糊控制算法的目的是因为分级控制能够显著的减少模糊控制算法的规则数，此分级模糊控制算法不仅简化了多变量系统的模糊控制设计，而且还有效的解决了系统变量之间的耦合问题。提高了球磨机制粉系统模糊控制算法的自适应能力。本文对分级模糊控制在盘县电厂200MW机组I/A Series DCS集散控制系统中的应用进行了分析和研究，设计了分级模糊控制器在I/A Series DCS上的挂接方案和通讯方案，并通过对控制功能的分析能够得到良好的控制效果，能够提高制粉系统运行的经济性和安全性，有着良好的工程应用前景和价值。
The ball mill pulverizing system is a MIMO system with strong coupling, long time delay and time changing apparently. With traditional PID control system, the controlling result is not so satisfying. Thus, manual control system has been put into use for a long time. However it is still an urgent problem to be solved that how to realize the automatic control of the steel ball mill pulverizing system, how to raise the level of automation and the efficiency of the system, and how to reduce the workers' labor intensity. This paper gives a thorough research work on the control of the steel ball mill pulverizing system from the angle of the intellectual control.
The control of the ball mill pulverizing system in the 200MW unit in PanXian power plant is researched in this paper. Fuzzy control police most has application in the situation that it is difficult to establish object model. It has better stability and robustness. In allusion to the characteristic of ball mill that it is simple lag, serious inertia and nonlinear, and general control methods are hard to gain a good control impact, so a fuzzy control model is held up which is graded according to burthen, temperature of outlet, negative pressure of entry, and the coupling characteristic of the model is analyzed. Finally a fuzzy control system is designed as the model. This theory can remarkable reduce the rule number of the fuzzy control algorithm. It can not only simplify the design for multi-variables system's fuzzy control, but also solve effectively the coupling problem between variables in the system, To raise the method' self-adaptability. And these papers analyze and study the method's application in the
I/A Series DCS control system in PanXian power plants. Devised coupling precepts and communicate precepts about graded fuzzy controller in the I/A Series DCS. It can gain favorable control effect by annalyzing control function and improve the economy and security of the pulverizing system. It has a favorable engineering applied foreground and value.
引文
[1]徐宁，中储式球磨机制粉系统实用的自动控制策略，论文，1998
[2]王东风，李遵基 中间储仓式制粉全程控制系统设计与应用，华东电力，1999，27(5)：41-43
[3]周海平等，钢球磨中间仓储式制粉系统的计算机优化控制技术和应用，中国电力，1994，27(9)：27-31
[4]李遵基等，中间仓储式制粉系统球磨机模糊控制理论与实践，中国电力，1996(29)10：33-37
[5]吕剑虹、沈炯，扬榕等，中间仓储式制粉系统控制策略研究及应用，中国电力，2000，33(9)：57-61
[6]章兢，童调生，庄斌，球磨机仿人模糊控制，电工技术学报，1998。13(2)：55-58
[7]刘军等，国产200MW制粉系统微机自动控制研究，电子技术，1990，23(8)：47-50
[8]刘齐寿，黄锦涛，贺刚，联国均，孙实文，球磨机中储式制粉系统系统自寻优控制，西安交大学报，2000，34(7)：30-34
[9]张彦武，贾立新，杨波，樊少华，自寻优—模糊控制策略在球蘑机控制中的实现，电力系统自动化，1999，23(17)23-34
[10]张栾英等，钢球磨煤机的自寻优控制技术，华北电力学院学报，1993，(4)
[11]李遵基，张国立，蔡军，章礼道，李存章，鲁敏，中储式球磨机制份系统模糊控制算法研究，华北电力学院学报，1995，22(2)
[12]邓依群等，球磨机计算机控制系统，中国电力，1998，31(3)：47-51
[13]容銮恩，刘志敏，袁振福，田子平。电站锅炉原理，中国电力出版社，1997
[14]李士勇，模糊控制和智能控制理论及应用[M]，哈尔滨哈尔滨工业大学出版社，1990
[15]李友善等。模糊控制理论及其在过程控制中的应用[M]，北京国防工业出版社 1993
[16]李卓，一种控制规则在线自调整模糊控制器，自动化仪表1996 17 94-6。
[17]J.R. GRACE A.A.AVIDAN T.M.KNOWLTON(1997). Circulating Fluidized Beds. BLACKIE ACADEMIC & PROFESSIONAL
[18]Abed. R.(1984)The characterization of turbulent fluid bed hydroynamics. In Fludizafion (ed.D.Kunii and R. Toei). Engineering Foundation. New York
[19]Amos. G.Rhodes.M.J.and Mineo.H.(1993)Gas mixing in gas-solids risers. Chem. Eng. Sci.48
[20]Gidaspow. D.(1994)Multiphaase Flow and Fluidizafion. Continuum and Kinetic Theory Description. Academic Press, San Diego
[21]Edwards.M.and Avaid. A.(1986)Conversion model aids scale-up of Mobil's fluid-bed MTG
process Chem. Eng. Sci.41
[22]李友善，李军．模糊控制理论及其在过程控制中的应用[M]．国防工业出版社，1993．
[23]YagerRR. Ona Hierarchical Stmcturefor Fuzzy Modelingand Control [J]. IEEE Trans. On Systems, Manand Cyber-netics, 1993, 23(4): 1189～1197.
[24]Adaptive Hierarchical Fuzzy Controller [J]. IEEE Trans. on System, Manand Cybernetics, 1993,23 (4):973～980.
[25]章卫国，扬向忠．模糊控制理论与应用[M]．西北工业大学出版社，1999．
[26]梁伟平．球磨机制粉系统智能控制算法的研究及应用[D]．华北电力大学博士论文，2000．
[27]龙升照，汪培庄．Fuzzy控制规则的自调整问题．模糊数学．1982，3，105～1122 李友善等．模糊控制理论及其在过程控制中的应用．国防工业出版社，1993．
[28]LindensD.AJ.Nie.Auni fiedreal-time approximate reasoning approach for use inintelligent control-Part2
[29]Application to multi variable blood pressure control .Int. J.control, 1992, 56(2), 365～397
[30]Medsker L. R. Hybrid Neural Network and Expert Systems. Kluwer Academic Publisher.Boston. 1994
[31]Myers W.Elaine Rich谈专家系统与神经网络能够结合在一起．计算机科学．1991．No．5．PP．1—3
[32]Callant S I. Connectionist Expert systems · Communication of the ACM. 1988. No.31. pp.152—169
[33]Xin Yao. Evolving Artificial Neural Network-PROCEEDINGS OF THE IEEE. Sep, 1999.Vol.87. No.9.. pp. 1423—1439
[34]Horikawa S, et al. On fuzzy modelling using fuzzy nerual networks with BP algorithm. IEEE Trans. Neural Networks. 1992. No.2
[35]Kong S G, Kosko B-Adptive fuzzy system for backing up a truck-and-tailer IEEE Trans. Neural Networks. 1992. No.2
[36]Jang J S. ANFIS: adptive-network-based fuzzy inference system. IEEE Trans. System, Man and Cybernet. 1993. No.3
[37]余明群，王耀南．智能模拟神经网络的发展新动向．模式识别与人工智能．Sept，1999．Vol．12．No．3．pp．3
[38]Tsoakalas L.et al. -Hybrid Expert System-Neural Network Methodlogy for Neural Plant Monitoring and Diagnostics, SPIE, 1990, Vol. 12, 93, Apple of AI Ⅷ
[39]王长林，李明．模糊控制理论在冶金转炉中的控制应用 工业出版社，1995。
[40]路敬．模糊控制与非模糊化的因子处理分析 电子控制技术，1998．
[41]Ahmed Rubaai, Daniel Ricketts, and M. David Kankam,et al., Experimental Verification of a
Hybrid Fuzzy Control Strategy for a High-Performance Brushless DC Drive System, IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 37, NO. 2, MARCH/APRIL 2001,503-512
[42] H. D. Tuan, P. Apkarian, T. Narikiyo, Parameterized Linear Matrix Inequality Techniques in Fuzzy Control System Design, IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 9, NO.2, APRIL 2001,324-332
[43] Ho Jae Lee, Jin Bae Park, and Guanrong Chen, Robust Fuzzy Control of Nonlinear Systems with Parametric Uncertainties, IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 9, NO. 2, APRIL 2001, 369-379
[44] Euntai Kim, A New Approach to Numerical Stability Analysis of Fuzzy Control Systems, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART C: APPLICATIONS AND REVIEWS, VOL. 31, NO. 1, FEBRUARY 2001, 107-113
[45] Zhang Yi and Pheng Ann Heng, Stability of Fuzzy Control Systems With Bounded Uncertain Delays, IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 10, NO. 1, FEBRUARY 2002,92-97
[46] T. John Koo, Stable Model Reference Adaptive Fuzzy Control of a Class of Nonlinear Systems,IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 9, NO. 4, AUGUST 2001, 624-636
[2]王东风，李遵基 中间储仓式制粉全程控制系统设计与应用，华东电力，1999，27(5)：41-43
[3]周海平等，钢球磨中间仓储式制粉系统的计算机优化控制技术和应用，中国电力，1994，27(9)：27-31
[4]李遵基等，中间仓储式制粉系统球磨机模糊控制理论与实践，中国电力，1996(29)10：33-37
[5]吕剑虹、沈炯，扬榕等，中间仓储式制粉系统控制策略研究及应用，中国电力，2000，33(9)：57-61
[6]章兢，童调生，庄斌，球磨机仿人模糊控制，电工技术学报，1998。13(2)：55-58
[7]刘军等，国产200MW制粉系统微机自动控制研究，电子技术，1990，23(8)：47-50
[8]刘齐寿，黄锦涛，贺刚，联国均，孙实文，球磨机中储式制粉系统系统自寻优控制，西安交大学报，2000，34(7)：30-34
[9]张彦武，贾立新，杨波，樊少华，自寻优—模糊控制策略在球蘑机控制中的实现，电力系统自动化，1999，23(17)23-34
[10]张栾英等，钢球磨煤机的自寻优控制技术，华北电力学院学报，1993，(4)
[11]李遵基，张国立，蔡军，章礼道，李存章，鲁敏，中储式球磨机制份系统模糊控制算法研究，华北电力学院学报，1995，22(2)
[12]邓依群等，球磨机计算机控制系统，中国电力，1998，31(3)：47-51
[13]容銮恩，刘志敏，袁振福，田子平。电站锅炉原理，中国电力出版社，1997
[14]李士勇，模糊控制和智能控制理论及应用[M]，哈尔滨哈尔滨工业大学出版社，1990
[15]李友善等。模糊控制理论及其在过程控制中的应用[M]，北京国防工业出版社 1993
[16]李卓，一种控制规则在线自调整模糊控制器，自动化仪表1996 17 94-6。
[17]J.R. GRACE A.A.AVIDAN T.M.KNOWLTON(1997). Circulating Fluidized Beds. BLACKIE ACADEMIC & PROFESSIONAL
[18]Abed. R.(1984)The characterization of turbulent fluid bed hydroynamics. In Fludizafion (ed.D.Kunii and R. Toei). Engineering Foundation. New York
[19]Amos. G.Rhodes.M.J.and Mineo.H.(1993)Gas mixing in gas-solids risers. Chem. Eng. Sci.48
[20]Gidaspow. D.(1994)Multiphaase Flow and Fluidizafion. Continuum and Kinetic Theory Description. Academic Press, San Diego
[21]Edwards.M.and Avaid. A.(1986)Conversion model aids scale-up of Mobil's fluid-bed MTG
process Chem. Eng. Sci.41
[22]李友善，李军．模糊控制理论及其在过程控制中的应用[M]．国防工业出版社，1993．
[23]YagerRR. Ona Hierarchical Stmcturefor Fuzzy Modelingand Control [J]. IEEE Trans. On Systems, Manand Cyber-netics, 1993, 23(4): 1189～1197.
[24]Adaptive Hierarchical Fuzzy Controller [J]. IEEE Trans. on System, Manand Cybernetics, 1993,23 (4):973～980.
[25]章卫国，扬向忠．模糊控制理论与应用[M]．西北工业大学出版社，1999．
[26]梁伟平．球磨机制粉系统智能控制算法的研究及应用[D]．华北电力大学博士论文，2000．
[27]龙升照，汪培庄．Fuzzy控制规则的自调整问题．模糊数学．1982，3，105～1122 李友善等．模糊控制理论及其在过程控制中的应用．国防工业出版社，1993．
[28]LindensD.AJ.Nie.Auni fiedreal-time approximate reasoning approach for use inintelligent control-Part2
[29]Application to multi variable blood pressure control .Int. J.control, 1992, 56(2), 365～397
[30]Medsker L. R. Hybrid Neural Network and Expert Systems. Kluwer Academic Publisher.Boston. 1994
[31]Myers W.Elaine Rich谈专家系统与神经网络能够结合在一起．计算机科学．1991．No．5．PP．1—3
[32]Callant S I. Connectionist Expert systems · Communication of the ACM. 1988. No.31. pp.152—169
[33]Xin Yao. Evolving Artificial Neural Network-PROCEEDINGS OF THE IEEE. Sep, 1999.Vol.87. No.9.. pp. 1423—1439
[34]Horikawa S, et al. On fuzzy modelling using fuzzy nerual networks with BP algorithm. IEEE Trans. Neural Networks. 1992. No.2
[35]Kong S G, Kosko B-Adptive fuzzy system for backing up a truck-and-tailer IEEE Trans. Neural Networks. 1992. No.2
[36]Jang J S. ANFIS: adptive-network-based fuzzy inference system. IEEE Trans. System, Man and Cybernet. 1993. No.3
[37]余明群，王耀南．智能模拟神经网络的发展新动向．模式识别与人工智能．Sept，1999．Vol．12．No．3．pp．3
[38]Tsoakalas L.et al. -Hybrid Expert System-Neural Network Methodlogy for Neural Plant Monitoring and Diagnostics, SPIE, 1990, Vol. 12, 93, Apple of AI Ⅷ
[39]王长林，李明．模糊控制理论在冶金转炉中的控制应用 工业出版社，1995。
[40]路敬．模糊控制与非模糊化的因子处理分析 电子控制技术，1998．
[41]Ahmed Rubaai, Daniel Ricketts, and M. David Kankam,et al., Experimental Verification of a
Hybrid Fuzzy Control Strategy for a High-Performance Brushless DC Drive System, IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 37, NO. 2, MARCH/APRIL 2001,503-512
[42] H. D. Tuan, P. Apkarian, T. Narikiyo, Parameterized Linear Matrix Inequality Techniques in Fuzzy Control System Design, IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 9, NO.2, APRIL 2001,324-332
[43] Ho Jae Lee, Jin Bae Park, and Guanrong Chen, Robust Fuzzy Control of Nonlinear Systems with Parametric Uncertainties, IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 9, NO. 2, APRIL 2001, 369-379
[44] Euntai Kim, A New Approach to Numerical Stability Analysis of Fuzzy Control Systems, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART C: APPLICATIONS AND REVIEWS, VOL. 31, NO. 1, FEBRUARY 2001, 107-113
[45] Zhang Yi and Pheng Ann Heng, Stability of Fuzzy Control Systems With Bounded Uncertain Delays, IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 10, NO. 1, FEBRUARY 2002,92-97
[46] T. John Koo, Stable Model Reference Adaptive Fuzzy Control of a Class of Nonlinear Systems,IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 9, NO. 4, AUGUST 2001, 624-636