智能控制在石膏纤维板生产线中的研究
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摘要
石膏纤维板作为一种新型墙体材料，具有轻质、高效、防火、防潮、隔热、隔音等优点，这种新型材料具有广阔的发展前景。
石膏纤维板生产中最重要的环节是厚度控制。由于石膏纤维板厚度控制系统是一个复杂工业控制系统，对“设定值跟踪特性”和“干扰抑制特性”的要求很高，传统PID控制器的参数很难同时满足两方面的要求，因此控制效果不理想。针对这些问题，模糊控制取得了一些令人信服的成效，但同时也存在着一定的问题。因此，采用改进后的模糊控制方法来设计模糊控制器将有助于提高板厚控制系统的性能，改善石膏纤维板的产品质量。
本文以湖北三环墙体材料有限责任公司石膏纤维板生产线为研究背景，对生产线的工艺流程、厚度控制系统进行了认真的学习和研究，分析了连续式压机的工作原理和影响石膏纤维板厚度的主要因素。针对厚度控制系统中存在的时变性、非线性和不确定性问题，以及模糊控制中存在的隶属函数难以确定、稳态误差较大的缺点，通过对区间值模糊算法的分析研究，本文分别采用模糊匹配区间值模糊推理、相似度量区间值模糊推理、双向近似区间值模糊推理设计了三种石膏纤维板厚度控制器。通过仿真试验，验证了区间值模糊算法的有效性；通过和普通模糊控制器的仿真效果进行对比，体现了基于区间值模糊推理的控制器调整时间短、稳态误差小的优点。
最后，针对这三种区间值厚度控制器，对原有控制规则提出了改进方案：增加系统稳定点附近控制点，使稳定点附近控制作用细腻，这样会使系统稳态误差和超调量减小；同时，远离稳定点控制作用幅度增大，保证响应速度加快。通过仿真验证了改进方案的合理性与有效性。其中，基于双向近似区间值推理设计的石膏纤维板厚度控制器各项性能指标表现最优。
Gypsum fiber board, as a new type of walling material, has advantages of lightness, highefficiency, fire resistance, damp proof, heat and sound insulation, deciding its widely potentialprospect.
The core of gypsum fiber board manufacturing is thickness control. While thicknesscontrol system of gypsum fiber board is a complicated industrial control system, traditionalPID controller's parameters can't reach demanding of excellent property of set value trackingand disturbance restraining at the same time. Therefore, the control effect is unperfect. Aimedat these problems, fuzzy control has already got some compellent achievements, but it alsohas certain problems. Thus, the thesis gives a modified fuzzy control method to design fuzzycontrollers which will be helpful to improve performance of board thickness control systemand product quality of gypsum fiber board.
The thesis is based on product line of gypsum fiber board of San Huan Walling MaterialCo. Ltd of Hubei province, through which it gives researches on process flow and thicknesscontrol system, in addition, analyses working principles of continuous press machine andmain factors influencing gypsum fiber board's thickness. Whereas, thickness control systemhas problems of time variance, non-linearity and uncertainty, moreover, it's difficult to decidemembership functions of fuzzy control, which also has shortcoming of large steady state error.After researches about interval valued fuzzy algorithm, the thesis contributes three kinds ofthickness controllers of gypsum fiber board, adopting fuzzy reasoning methods of fuzzymatching interval value, similar measuring interval value and Bidirectional approximateinterval value. And simulation experiments prove the validation of interval valued fuzzyalgorithm. Compared to traditional fuzzy controllers about simulation effects, it shows thatfuzzy controllers based on interval valued fuzzy reasoning have advantages of short adjustingtime and little steady state error.
Finally, aimed at three interval valued thickness controllers mentioned above, improvedschemes are put forward about original control laws: adding control points nearby systemsteady point to make the control nearby steady point more exquisite, decreasing system steadyerror and overshoot. Simultaneously, control amplitude away from steady points increases,assuring response speed fast. Simulation proves the reasonableness and efficiency ofimproved scheme. Finally, thickness controller of gypsum fiber board based on Bidirectionalapproximate interval value has optimum effects in all performance points.
石膏纤维板生产中最重要的环节是厚度控制。由于石膏纤维板厚度控制系统是一个复杂工业控制系统，对“设定值跟踪特性”和“干扰抑制特性”的要求很高，传统PID控制器的参数很难同时满足两方面的要求，因此控制效果不理想。针对这些问题，模糊控制取得了一些令人信服的成效，但同时也存在着一定的问题。因此，采用改进后的模糊控制方法来设计模糊控制器将有助于提高板厚控制系统的性能，改善石膏纤维板的产品质量。
本文以湖北三环墙体材料有限责任公司石膏纤维板生产线为研究背景，对生产线的工艺流程、厚度控制系统进行了认真的学习和研究，分析了连续式压机的工作原理和影响石膏纤维板厚度的主要因素。针对厚度控制系统中存在的时变性、非线性和不确定性问题，以及模糊控制中存在的隶属函数难以确定、稳态误差较大的缺点，通过对区间值模糊算法的分析研究，本文分别采用模糊匹配区间值模糊推理、相似度量区间值模糊推理、双向近似区间值模糊推理设计了三种石膏纤维板厚度控制器。通过仿真试验，验证了区间值模糊算法的有效性；通过和普通模糊控制器的仿真效果进行对比，体现了基于区间值模糊推理的控制器调整时间短、稳态误差小的优点。
最后，针对这三种区间值厚度控制器，对原有控制规则提出了改进方案：增加系统稳定点附近控制点，使稳定点附近控制作用细腻，这样会使系统稳态误差和超调量减小；同时，远离稳定点控制作用幅度增大，保证响应速度加快。通过仿真验证了改进方案的合理性与有效性。其中，基于双向近似区间值推理设计的石膏纤维板厚度控制器各项性能指标表现最优。
Gypsum fiber board, as a new type of walling material, has advantages of lightness, highefficiency, fire resistance, damp proof, heat and sound insulation, deciding its widely potentialprospect.
The core of gypsum fiber board manufacturing is thickness control. While thicknesscontrol system of gypsum fiber board is a complicated industrial control system, traditionalPID controller's parameters can't reach demanding of excellent property of set value trackingand disturbance restraining at the same time. Therefore, the control effect is unperfect. Aimedat these problems, fuzzy control has already got some compellent achievements, but it alsohas certain problems. Thus, the thesis gives a modified fuzzy control method to design fuzzycontrollers which will be helpful to improve performance of board thickness control systemand product quality of gypsum fiber board.
The thesis is based on product line of gypsum fiber board of San Huan Walling MaterialCo. Ltd of Hubei province, through which it gives researches on process flow and thicknesscontrol system, in addition, analyses working principles of continuous press machine andmain factors influencing gypsum fiber board's thickness. Whereas, thickness control systemhas problems of time variance, non-linearity and uncertainty, moreover, it's difficult to decidemembership functions of fuzzy control, which also has shortcoming of large steady state error.After researches about interval valued fuzzy algorithm, the thesis contributes three kinds ofthickness controllers of gypsum fiber board, adopting fuzzy reasoning methods of fuzzymatching interval value, similar measuring interval value and Bidirectional approximateinterval value. And simulation experiments prove the validation of interval valued fuzzyalgorithm. Compared to traditional fuzzy controllers about simulation effects, it shows thatfuzzy controllers based on interval valued fuzzy reasoning have advantages of short adjustingtime and little steady state error.
Finally, aimed at three interval valued thickness controllers mentioned above, improvedschemes are put forward about original control laws: adding control points nearby systemsteady point to make the control nearby steady point more exquisite, decreasing system steadyerror and overshoot. Simultaneously, control amplitude away from steady points increases,assuring response speed fast. Simulation proves the reasonableness and efficiency ofimproved scheme. Finally, thickness controller of gypsum fiber board based on Bidirectionalapproximate interval value has optimum effects in all performance points.
引文
[1] 陈福广，沈荣熹，徐洛屹．新型墙体材料手册．北京：中国建材工业出版社，2000．
[2] 赵渠森编译．复合材料．北京：国防工业出版社，1985．
[3] Egon f K, Karsten H L. Gypsum Fiberboard History and Outlook. Bonded Wood and Fiber Composite Materials, Forest Products Society(USA), 1991:77-84.
[4] 蒋志全．均质石膏纤维板的生产与应用．房材与应用，1999，(5)：36-38．
[5] 叶宪文．石膏纤维板在建筑上的应用．木材工业，2002，16(3)：26-27．
[6] 何水清．国外新型建材发展的回顾与展望．国外建材，2004，(2)：66-69．
[7] 金艳春，孙立人．石膏纤维板生产技术．林业科技情报，2003，(02)：67．
[8] 徐燮中．石膏纤维板生产工艺及设备简介．中国建材装备，1995，(1)：31-33．
[9] 黄菊花，肖安，许益民．连续平压机板厚控制液压系统．南昌大学学报，1999，(2)：80-85．
[10] 董军红．厚度控制方式的对比及应用．新疆有色金属，2001，(2)：54-56．
[11] 羊文伟，孙承业．穿透网带式干燥机及干燥特点．中国农机化，1997，(1)：143-145．
[12] 张宜生，陈士英，龙玲．半干法石膏纤维板工艺研究．木材工业，1998，12(5)：8-11．
[13] 白宏成，何晶晶，周建中．石膏板生产线计算机监控系统．中国建材科技，2000，(3)：32-36．
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[19] Marinos P N. Fuzzy Logic. Information and Control, 1966, 7(1):315-324.
[20] Guguen B. G. Logic Problems on Fuzzy Notion. Information and Control, 1969, 3(2):25-39.
[21] Zadeh L A. Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on Systems, Man and Cybernetics, 1973(1):28-44.
[22] Mamdani E H. Application of fuzzy aigorithms for simple dynamic plant. Proceeding IEE, 1974, 121(12): 1585-1588.
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[25] 梁铁城，姜长洪．参数自调整模糊控制系统的设计与仿真．系统仿真学报，2006，18(s2)：628-633．
[26] 王大庆，黄勇，丁崇生．一类模型参考模糊自适应控制器的研究．机床与液压，2001，(5)：49-52．
[27] 黄传明，王忠勇，方千山．基于模糊逻辑参考模型自适应控制系统．华北科技学院学报，2006，(01)：88-91．
[28] 戴学丰，孙立宁．自组织模糊控制及在机器人中的应用．电机与控制学报．2005，(5)：90-94．
[29] Wakileh B A M, Gill K F. Robot Control Using Self-OrganizingFuzzy Logic. Computer in Industry, 1990, 15(3):175-186.
[30] 管萍，陈家斌，刘晓河．基于滑模控制的挠性卫星的自学习模糊控制．北京理工大学学报，2005，(2)：36-39．
[31] 何小宁，肖伸平，王兵．多变量模糊控制系统的结构分解及其应用．计算机测量与控制，2005，(5)：54-56．
[32] 王丽梅，田明秀，王力．永磁同步电动机的神经网络模糊控制器设计．电气传动，2006，36(8)：34-37．
[33] 段萍，张建畅，丁承君．基于模糊遗传算法的移动机器人墙跟踪控制策略．控制理论与应用，2006，23(3)：416-420．
[34] 刘彬，白沁园，杨风禄．专家模糊控制在锅炉床温控制中的应用．电气传动自动化，2005，27(4)：58-60．
[35] Takak T, Sugeno M. Fuzzy Identification of Systems It Applications to Modeling and Control. IEEE Trans. on SMC, 1985, 15(1):116—132.
[36] Turksen I B. Representation of connectives in fuzzy reasoning: The view through normalform. IEEE Trans Systems Man Cybernet, 1984, 14:146-151.
[37] Turksen I B. Interval valued fuzzy sets based on normal forms. Fuzzy Sets and Systems, 1986, 20:191-210.
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[39] 吴望名．区间值模糊集和区间值模糊推理．模糊系统与数学，1992，6：38-48．
[40] 吴望名．模糊推理的原则与应用．贵阳：贵州科技出版社，1994：250-284．
[41] 李凡．一个有效的区间值模糊推理方法．应用科学学报，2000，4：327-330．
[42] 李凡，徐章艳，卢安．基于Vague集的插值模糊推理，应用科学学报，2001，2：69-72．
[43] 李凡，徐章艳，吕泽华．一种基于Vague集相似度量的近似推理方法．计算机工程与科学，2002，24(5)：107-110．
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[54] Chen S M,Hsiao W H.Bidirectional approximate reasoning for rule-based systems using interval-valued fuzzy sets.Fuzzy Sets and Systems,2000,113(2) :185-203．
[2] 赵渠森编译．复合材料．北京：国防工业出版社，1985．
[3] Egon f K, Karsten H L. Gypsum Fiberboard History and Outlook. Bonded Wood and Fiber Composite Materials, Forest Products Society(USA), 1991:77-84.
[4] 蒋志全．均质石膏纤维板的生产与应用．房材与应用，1999，(5)：36-38．
[5] 叶宪文．石膏纤维板在建筑上的应用．木材工业，2002，16(3)：26-27．
[6] 何水清．国外新型建材发展的回顾与展望．国外建材，2004，(2)：66-69．
[7] 金艳春，孙立人．石膏纤维板生产技术．林业科技情报，2003，(02)：67．
[8] 徐燮中．石膏纤维板生产工艺及设备简介．中国建材装备，1995，(1)：31-33．
[9] 黄菊花，肖安，许益民．连续平压机板厚控制液压系统．南昌大学学报，1999，(2)：80-85．
[10] 董军红．厚度控制方式的对比及应用．新疆有色金属，2001，(2)：54-56．
[11] 羊文伟，孙承业．穿透网带式干燥机及干燥特点．中国农机化，1997，(1)：143-145．
[12] 张宜生，陈士英，龙玲．半干法石膏纤维板工艺研究．木材工业，1998，12(5)：8-11．
[13] 白宏成，何晶晶，周建中．石膏板生产线计算机监控系统．中国建材科技，2000，(3)：32-36．
[14] Damon C. Cutting with High Pressure Water and Abrasives. 27th International Abrasive Symposium, 1989:92-105.
[15] 池金香，赵兴银．纸面石膏板的干燥与控制．建材科技，1994，(11)：27-28．
[16] 张泉，宁夏．影响板带厚度因素和板厚控制方法．现代技能开发，2002，(7)：96．
[17] Zadeh L A. Fuzzy Sets. Information and Control, 1965, 8(3):338-353.
[18] Zadeh L A. Fuzzy Set and System. Proc. Symp. on system theory. Polytech. Inst. Brooklyn, NewYork, 1965: 29-37.
[19] Marinos P N. Fuzzy Logic. Information and Control, 1966, 7(1):315-324.
[20] Guguen B. G. Logic Problems on Fuzzy Notion. Information and Control, 1969, 3(2):25-39.
[21] Zadeh L A. Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on Systems, Man and Cybernetics, 1973(1):28-44.
[22] Mamdani E H. Application of fuzzy aigorithms for simple dynamic plant. Proceeding IEE, 1974, 121(12): 1585-1588.
[23] Procyk T J, Mamdani E H. A Linguistic Self-Organizing Process Controller. Automatica, 1979, 15(1):15-30.
[24] 宋子巍，陈思忠，杨林．模糊-PID控制的MATLAB仿真分析．科技资讯，2006，(3)：3-4．
[25] 梁铁城，姜长洪．参数自调整模糊控制系统的设计与仿真．系统仿真学报，2006，18(s2)：628-633．
[26] 王大庆，黄勇，丁崇生．一类模型参考模糊自适应控制器的研究．机床与液压，2001，(5)：49-52．
[27] 黄传明，王忠勇，方千山．基于模糊逻辑参考模型自适应控制系统．华北科技学院学报，2006，(01)：88-91．
[28] 戴学丰，孙立宁．自组织模糊控制及在机器人中的应用．电机与控制学报．2005，(5)：90-94．
[29] Wakileh B A M, Gill K F. Robot Control Using Self-OrganizingFuzzy Logic. Computer in Industry, 1990, 15(3):175-186.
[30] 管萍，陈家斌，刘晓河．基于滑模控制的挠性卫星的自学习模糊控制．北京理工大学学报，2005，(2)：36-39．
[31] 何小宁，肖伸平，王兵．多变量模糊控制系统的结构分解及其应用．计算机测量与控制，2005，(5)：54-56．
[32] 王丽梅，田明秀，王力．永磁同步电动机的神经网络模糊控制器设计．电气传动，2006，36(8)：34-37．
[33] 段萍，张建畅，丁承君．基于模糊遗传算法的移动机器人墙跟踪控制策略．控制理论与应用，2006，23(3)：416-420．
[34] 刘彬，白沁园，杨风禄．专家模糊控制在锅炉床温控制中的应用．电气传动自动化，2005，27(4)：58-60．
[35] Takak T, Sugeno M. Fuzzy Identification of Systems It Applications to Modeling and Control. IEEE Trans. on SMC, 1985, 15(1):116—132.
[36] Turksen I B. Representation of connectives in fuzzy reasoning: The view through normalform. IEEE Trans Systems Man Cybernet, 1984, 14:146-151.
[37] Turksen I B. Interval valued fuzzy sets based on normal forms. Fuzzy Sets and Systems, 1986, 20:191-210.
[38] Gorzalczany M B. A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets and Systems, 1987, 21(1): 1-17.
[39] 吴望名．区间值模糊集和区间值模糊推理．模糊系统与数学，1992，6：38-48．
[40] 吴望名．模糊推理的原则与应用．贵阳：贵州科技出版社，1994：250-284．
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