弹簧钢丝热处理控制系统及其控制策略研究
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摘要
模糊控制作为智能控制的最主要形式被广泛地应用于工业生产的各个领域，但是模糊控制精度不高却是不争的事实，提高模糊控制的精度、消除振荡成为模糊控制发展的新课题，为此，模糊控制的研究者提出了各种解决问题的办法，为模糊控制技术的进一步推广起到很重要的作用；对于大惯性的纯滞后系统实施的预测控制也是控制界的主要课题之一，传统的Smith预估器需要对象的精确数学模型，而实际工程中的控制对象往往很难获得其精确数学模型，因此，控制精度高且具有预测功能的模糊控制器是解决这一大类问题首选控制方案。
弹簧钢丝对于钢丝的韧性、弹性、强度等均有较高的要求，而这些性能参数取决于生产工艺的实现，稳定，无抖动的温度控制技术成为提高弹簧钢丝质量的关键技术。本文以湖北某钢丝绳厂弹簧钢丝热处理生产线控制系统为依托，论述了整个生产过程的监控系统的设计，通过对该类钢丝生产中的快速加热过程、退火、回火等过程中的温度控制参数的研究，设计了相应的智能型复合模糊控制器，根据快速加热过程的实现方式，对于快速反应的被控对象，给出了以模糊控制为基础的结合开关控制、PI控制的快速升温，且不超调的一种智能型复合模糊控制器，对于退火、回火等工艺过程，采用电加热方式，该类工艺过程作为控制对象属于具有纯滞后的大惯性系统，作者设计出模型预测自适应模糊控制器，并对所设计的控制器进行计算机仿真实验，取得了满意的效果。
总之，控制系统不需要被控对旁的精确数学模型，采用以上控制策略，即可获得较好的控制效果。可以推广应用到其它类似的生产工艺中。
Fuzzy control, as a main way of intelligent control, is widely used in every field of industrial production, but it is undisputable that fuzzy control has no high precision. The increasement of precision and elimination of vibration for fuzzy control is a new topic to develop fuzzy controller. Thus, the researcher of fuzzy control has proposed various programs to solve the problems of this kind, which plays an important role in popularization of fuzzy control technology. The predictive control employed in a pure delay system with big inertia is also a major issue in control arena. The traditional predictors such as Smith require a precise mathematic model of object, but practically, it is very difficult for a control object to obtain a precise mathematic model. So, fuzzy controller with high precision and prediction ability is a first priority
Spring steel-wire has higher toughness, elasticity and strength, and these parameters of steel wire depend on its manufacturing process. Hence, a steady or in-fluctuation temperature control technology is a key role to improve the quality of spring steel-wire. Based on the heating treatment control system of a spring steel - wire production line in a factory, Hubei province, the paper deals with the design of fully automatically monitoring system across its manufacturing process. Through research of parameters of temperature control during the period of heating, annealing and tempering in steel wire manufacturing process, the corresponding composite intelligence fuzzy controller is designed. In light with the way of fast heating, a composite intelligent fuzzy controller combined with on-off control & PI control is set up. For the control object that adopts electricity heating to anneal and temper, lying in a pure delay system with big inertia, the author designed an adaptive predicative fuzzy controller. Moreover, the simulation test on the designed controller with the tool SIMULINK was conducted, and some satisfied results were got.
In conclusion, the designed controller needs no precise t mathematics model of the controlled object, when the mentioned programs are adopted, the satisfied simulation results can be obtained, the achievements of the paper can be put into operation in the other simaliar product.
弹簧钢丝对于钢丝的韧性、弹性、强度等均有较高的要求，而这些性能参数取决于生产工艺的实现，稳定，无抖动的温度控制技术成为提高弹簧钢丝质量的关键技术。本文以湖北某钢丝绳厂弹簧钢丝热处理生产线控制系统为依托，论述了整个生产过程的监控系统的设计，通过对该类钢丝生产中的快速加热过程、退火、回火等过程中的温度控制参数的研究，设计了相应的智能型复合模糊控制器，根据快速加热过程的实现方式，对于快速反应的被控对象，给出了以模糊控制为基础的结合开关控制、PI控制的快速升温，且不超调的一种智能型复合模糊控制器，对于退火、回火等工艺过程，采用电加热方式，该类工艺过程作为控制对象属于具有纯滞后的大惯性系统，作者设计出模型预测自适应模糊控制器，并对所设计的控制器进行计算机仿真实验，取得了满意的效果。
总之，控制系统不需要被控对旁的精确数学模型，采用以上控制策略，即可获得较好的控制效果。可以推广应用到其它类似的生产工艺中。
Fuzzy control, as a main way of intelligent control, is widely used in every field of industrial production, but it is undisputable that fuzzy control has no high precision. The increasement of precision and elimination of vibration for fuzzy control is a new topic to develop fuzzy controller. Thus, the researcher of fuzzy control has proposed various programs to solve the problems of this kind, which plays an important role in popularization of fuzzy control technology. The predictive control employed in a pure delay system with big inertia is also a major issue in control arena. The traditional predictors such as Smith require a precise mathematic model of object, but practically, it is very difficult for a control object to obtain a precise mathematic model. So, fuzzy controller with high precision and prediction ability is a first priority
Spring steel-wire has higher toughness, elasticity and strength, and these parameters of steel wire depend on its manufacturing process. Hence, a steady or in-fluctuation temperature control technology is a key role to improve the quality of spring steel-wire. Based on the heating treatment control system of a spring steel - wire production line in a factory, Hubei province, the paper deals with the design of fully automatically monitoring system across its manufacturing process. Through research of parameters of temperature control during the period of heating, annealing and tempering in steel wire manufacturing process, the corresponding composite intelligence fuzzy controller is designed. In light with the way of fast heating, a composite intelligent fuzzy controller combined with on-off control & PI control is set up. For the control object that adopts electricity heating to anneal and temper, lying in a pure delay system with big inertia, the author designed an adaptive predicative fuzzy controller. Moreover, the simulation test on the designed controller with the tool SIMULINK was conducted, and some satisfied results were got.
In conclusion, the designed controller needs no precise t mathematics model of the controlled object, when the mentioned programs are adopted, the satisfied simulation results can be obtained, the achievements of the paper can be put into operation in the other simaliar product.
引文
[1] 李士勇．模糊控制·神经控制和智能控制论，哈尔滨：哈尔滨工业大学出版社，1998
[2] Taksgi, T. and Sugeno, M. Fuzzy Identification of System and Its Applications to Modeling and Control. IEEE Trans. Systems, Man, and Cybernetics, 1985(15): 116-132
[3] Chair, P, A. Defining Intelligent Control. IEEE Control System Magazine, 1994, (14): 4-5, 58-66;
[4] Zadeh. L.A. Fuzzy Sets and Their Applications. New york: Academic Press, 1975;
[5] 赵发忠．我国弹簧钢丝生产现状与发展战略．金属制品，No．2，1-3．2004
[6] 雷延权，傅家骐．金属热处理工艺方法500种，北京：机械工业出版社，1998
[7] 姜桂良，念远征，杜瑞青．压力容器缠绕用扁钢丝生产工艺探讨．金属制品，No．2 29-31，2000
[8] 吕桂清．超长银亮钢丝生产工艺研究．金属制品，No．3 9-11，2001
[9] 张恩勤，施松椒，高卫华，翁正新．模糊控制系统近年来的研究与发展．控制理论与应用，No．1，7-11．2001
[10] 刘曙光，魏俊民，竺志超．模糊控制技术，纺织工业出版社
[11] 张玮，宋年年．提高模糊控制精度的研究现状
[12] 陈永义，我国模糊控制技术标准化工作现状．
[13] 曹勇．锌铝合金镀层钢丝生产．金属制品，No．2 12-13，2002
[14] 周畅，朱德森，陈绵云，姜波．一种新型复合模糊控制器的设计及应用．信息与控制，No．2 102-107，2003
[15] Landau I.D.A. Survey of Model Reference Adaptive Techniques. Theory and Applications Automatics, 1974. 11 P759-768
[16] Shanley A.. Advanced Process Control. Chen. Eng., 1995. 5: P28
[17] 汪晓光，孙晓英，陈英赫．应用国产组态软件包-组态王开发立体仓仿真系统．电子技术与应用，No．5 16-19．1999
[18] 王常力，罗安．集散型控制系统及其选型，北京：清华大学出版社，1996
[19] 袁任光．集散型科学出版社控制系统应用技术实例
[20] 王立新．自适应模糊系统与控制，国防工业出版社
[21] 王大庆，黄勇，丁崇生，王花玲．一类模型参考自适应控制起的研究．机床与液压，No．5，49-52，2001
[22] 徐英，徐用懋，杨耳辅．时变大纯滞后系统的单神经元预测控制．清华大学学报，No．3 383-386，2002
[23] 吴庆华，任长明，杨博，谢亚利．一种自组织模糊控制算法及实现．天津大学学报 319-323，1999；
[24] 刘晓霞，田兆福，孙金根，张玉春．时滞系统的自适应模糊控制器的研究．信息与控制，No．3，285-288，2003
[25] 施阳等．MATLAB语言精要及动态仿真工具SIMULINK，西安：西北工业大学出版社，1997
[26] 李人厚，张平安．精通MATLAB综合辅导与指南，西安：西安交通大学出版社，1998
[27] 宋安谰．MATLAB6．5辅助优化设计与计算，北京：机械工业出版社
[28] 魏克新，王之亮，陈志敏．MATLAB语言与自动控制系统设计，
[29] 薛定宇，陈阳泉．基于MATLAB／SIMULINK的系统仿真技术，北京：清华大学出版社
[30] 王立新．模糊系统：挑战与机遇并存．自动化学报，No．4 585-590，2002
[31] 李洪兴．变论域自适应模糊控制器．中国科学，No．1 32-42，1999
[32] 姜玉宪．控制系统仿真．北京：北京航空航天大学出版社，1998
[2] Taksgi, T. and Sugeno, M. Fuzzy Identification of System and Its Applications to Modeling and Control. IEEE Trans. Systems, Man, and Cybernetics, 1985(15): 116-132
[3] Chair, P, A. Defining Intelligent Control. IEEE Control System Magazine, 1994, (14): 4-5, 58-66;
[4] Zadeh. L.A. Fuzzy Sets and Their Applications. New york: Academic Press, 1975;
[5] 赵发忠．我国弹簧钢丝生产现状与发展战略．金属制品，No．2，1-3．2004
[6] 雷延权，傅家骐．金属热处理工艺方法500种，北京：机械工业出版社，1998
[7] 姜桂良，念远征，杜瑞青．压力容器缠绕用扁钢丝生产工艺探讨．金属制品，No．2 29-31，2000
[8] 吕桂清．超长银亮钢丝生产工艺研究．金属制品，No．3 9-11，2001
[9] 张恩勤，施松椒，高卫华，翁正新．模糊控制系统近年来的研究与发展．控制理论与应用，No．1，7-11．2001
[10] 刘曙光，魏俊民，竺志超．模糊控制技术，纺织工业出版社
[11] 张玮，宋年年．提高模糊控制精度的研究现状
[12] 陈永义，我国模糊控制技术标准化工作现状．
[13] 曹勇．锌铝合金镀层钢丝生产．金属制品，No．2 12-13，2002
[14] 周畅，朱德森，陈绵云，姜波．一种新型复合模糊控制器的设计及应用．信息与控制，No．2 102-107，2003
[15] Landau I.D.A. Survey of Model Reference Adaptive Techniques. Theory and Applications Automatics, 1974. 11 P759-768
[16] Shanley A.. Advanced Process Control. Chen. Eng., 1995. 5: P28
[17] 汪晓光，孙晓英，陈英赫．应用国产组态软件包-组态王开发立体仓仿真系统．电子技术与应用，No．5 16-19．1999
[18] 王常力，罗安．集散型控制系统及其选型，北京：清华大学出版社，1996
[19] 袁任光．集散型科学出版社控制系统应用技术实例
[20] 王立新．自适应模糊系统与控制，国防工业出版社
[21] 王大庆，黄勇，丁崇生，王花玲．一类模型参考自适应控制起的研究．机床与液压，No．5，49-52，2001
[22] 徐英，徐用懋，杨耳辅．时变大纯滞后系统的单神经元预测控制．清华大学学报，No．3 383-386，2002
[23] 吴庆华，任长明，杨博，谢亚利．一种自组织模糊控制算法及实现．天津大学学报 319-323，1999；
[24] 刘晓霞，田兆福，孙金根，张玉春．时滞系统的自适应模糊控制器的研究．信息与控制，No．3，285-288，2003
[25] 施阳等．MATLAB语言精要及动态仿真工具SIMULINK，西安：西北工业大学出版社，1997
[26] 李人厚，张平安．精通MATLAB综合辅导与指南，西安：西安交通大学出版社，1998
[27] 宋安谰．MATLAB6．5辅助优化设计与计算，北京：机械工业出版社
[28] 魏克新，王之亮，陈志敏．MATLAB语言与自动控制系统设计，
[29] 薛定宇，陈阳泉．基于MATLAB／SIMULINK的系统仿真技术，北京：清华大学出版社
[30] 王立新．模糊系统：挑战与机遇并存．自动化学报，No．4 585-590，2002
[31] 李洪兴．变论域自适应模糊控制器．中国科学，No．1 32-42，1999
[32] 姜玉宪．控制系统仿真．北京：北京航空航天大学出版社，1998
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