焦炉立火道温度的智能控制模型及仿真研究
|
摘要
焦炉具有大惯性、大时滞、强非线性、多因素耦合、变参数的特点,焦化过程是一个传热和化学变化过程,加上焦炉炉体结构复杂,操作条件恶劣,检测手段少,因此实现立火道温度控制有一定难度。焦炉立火道温度的稳定性直接关系到焦炭质量与焦炉生产成本,是焦炉加热燃烧过程控制的关键与核心。焦炉稳定均匀加热,对提高焦炉生产率和焦炭质量、降低能耗及延长焦炉寿命、减少炼焦生产中的环境污染有重大意义。
针对采集的焦炉蓄顶温度与立火道温度的时间系列数据,从定性和定量两个角度分析并论证了蓄顶温度与立火道温度之间有很强的线性关系。应用线性回归理论,建立了蓄顶温度与立火道温度的一元线性回归数学模型。基于蓄顶温度与立火道温度的一元线性回归数学模型,获得了大量立火道温度的时间系列数据,结合对应的煤气流量的时间系列数据,运用系统辨识理论,探讨了立火道温度与焦炉煤气流量的ARX模型,并采用最小二乘法原理离线估计其模型的参数。立火道温度系统采用的串级控制方案,分别以火道温度和煤气流量为主、副回路的被控参数。主回路为立火道温度优化控制回路,引入模糊控制技术保证火道温度稳定在目标立火道温度附近。副回路为阀门控制回路,保证现场的煤气流量稳定且跟随设定值,是主回路温度优化控制的基础。
应用MATLAB/Simulink仿真软件,分别对立火道温度智能控制模型进行了常规PID和模糊PID复合控制仿真研究。对仿真曲线进行了分析,结果表明:当外界条件因煤气流量或其他原因产生扰动时,模糊PID复合控制能更快的抑制扰动,有较高的鲁棒性并且温度的波动较小,调节的时间相对较短,验证了模糊PID复合控制控制算法的可行性和有效性,系统能够稳定炉温,有效提高了焦炭质量、降低能耗及延长焦炉寿命,达到了预期控制效果。
Coke oven is a system of large time-delay, big inertia, strong nonlinear, many factor couplings time-varying parameter.Coking is a heating passage and metamorphosis process ,as well as complicate body structure, bad operation condition ,few detecting means ,therefore flue temperature accuracy control has a certain degree of difficulty. The stability of flue temperature in coke oven is related to coke quality and cost of production directly, that is a key and core of the coke oven heating and burning process control. Stable and homogeneous heating in coke oven has a fundamental significance to improving efficacy and the quality of coke coke, reducing energy sources consuming and extending coke oven life-span, cutting down environmental pollution in coking process of producing.
By applying the linear regress theory, the relationship mode between flue temperature and top of regenerators’is built. By applying the system identification theory, the ARX mode between the flue temperature and the gas flow is established and its parameters of the mode are estimated by using the method of minimum two multiplication. Apply the basis cascade control theory, system adopts to flue temperature and coal flue gas flow as controlled parameters of host circuit and subsidiary circuit respectively.The host circuit is flue temperature optimization controlling circuit and the main effect is to ensure flue temperature stabilizing in target flue temperature nearby.By ultilizing the technology of fuzzy control, a fuzzy controller of setting gas flow is designed. The subsidiary circuit is a circuit of valve control, the main effect is to ensure that the scene coal gas flow keeping stable and following setting value , which is the basis controlling of the host circuit temperature optimiztion.
The routine PID control and compound Fuzzy-PID control of intelligent control model of flue temperature are simulated respectively by applying Matlab/Simulink. The simulating curves are analyzed , the result has indicated: when the external condition produces perturbation motion because of coal gas flow or other, compound Fuzzy-PID control can restraint perturbation motion more quickly with higher robustness , less temperature fluctuation and shorter measuring time. It has verified feasibility and validity of compound Fuzzy-PID control algolithm .It is able to stabilize furnace temperature , having an effect to improve the quality of coke , reducing energy consumption and extending coke oven life-span .It has reached expect control effect.
针对采集的焦炉蓄顶温度与立火道温度的时间系列数据,从定性和定量两个角度分析并论证了蓄顶温度与立火道温度之间有很强的线性关系。应用线性回归理论,建立了蓄顶温度与立火道温度的一元线性回归数学模型。基于蓄顶温度与立火道温度的一元线性回归数学模型,获得了大量立火道温度的时间系列数据,结合对应的煤气流量的时间系列数据,运用系统辨识理论,探讨了立火道温度与焦炉煤气流量的ARX模型,并采用最小二乘法原理离线估计其模型的参数。立火道温度系统采用的串级控制方案,分别以火道温度和煤气流量为主、副回路的被控参数。主回路为立火道温度优化控制回路,引入模糊控制技术保证火道温度稳定在目标立火道温度附近。副回路为阀门控制回路,保证现场的煤气流量稳定且跟随设定值,是主回路温度优化控制的基础。
应用MATLAB/Simulink仿真软件,分别对立火道温度智能控制模型进行了常规PID和模糊PID复合控制仿真研究。对仿真曲线进行了分析,结果表明:当外界条件因煤气流量或其他原因产生扰动时,模糊PID复合控制能更快的抑制扰动,有较高的鲁棒性并且温度的波动较小,调节的时间相对较短,验证了模糊PID复合控制控制算法的可行性和有效性,系统能够稳定炉温,有效提高了焦炭质量、降低能耗及延长焦炉寿命,达到了预期控制效果。
Coke oven is a system of large time-delay, big inertia, strong nonlinear, many factor couplings time-varying parameter.Coking is a heating passage and metamorphosis process ,as well as complicate body structure, bad operation condition ,few detecting means ,therefore flue temperature accuracy control has a certain degree of difficulty. The stability of flue temperature in coke oven is related to coke quality and cost of production directly, that is a key and core of the coke oven heating and burning process control. Stable and homogeneous heating in coke oven has a fundamental significance to improving efficacy and the quality of coke coke, reducing energy sources consuming and extending coke oven life-span, cutting down environmental pollution in coking process of producing.
By applying the linear regress theory, the relationship mode between flue temperature and top of regenerators’is built. By applying the system identification theory, the ARX mode between the flue temperature and the gas flow is established and its parameters of the mode are estimated by using the method of minimum two multiplication. Apply the basis cascade control theory, system adopts to flue temperature and coal flue gas flow as controlled parameters of host circuit and subsidiary circuit respectively.The host circuit is flue temperature optimization controlling circuit and the main effect is to ensure flue temperature stabilizing in target flue temperature nearby.By ultilizing the technology of fuzzy control, a fuzzy controller of setting gas flow is designed. The subsidiary circuit is a circuit of valve control, the main effect is to ensure that the scene coal gas flow keeping stable and following setting value , which is the basis controlling of the host circuit temperature optimiztion.
The routine PID control and compound Fuzzy-PID control of intelligent control model of flue temperature are simulated respectively by applying Matlab/Simulink. The simulating curves are analyzed , the result has indicated: when the external condition produces perturbation motion because of coal gas flow or other, compound Fuzzy-PID control can restraint perturbation motion more quickly with higher robustness , less temperature fluctuation and shorter measuring time. It has verified feasibility and validity of compound Fuzzy-PID control algolithm .It is able to stabilize furnace temperature , having an effect to improve the quality of coke , reducing energy consumption and extending coke oven life-span .It has reached expect control effect.
引文
[1]吴宏博,朱宏祥,王新立等.焦炉加热过程计算机控制的现状与发展[J].冶金自动2000,24(6):7～10
[2]吴敏,刘永霞,曹卫华等.焦炉加热燃烧过程智能优化控制系统的研究及应用(上)[J].冶金自动化 ,2006,(5):25～28
[3]姚昭章.炼焦学[M].北京:冶金工业出版社,1995
[4]高宪文,赵亚平.模糊自适应PID在焦炉温度控制中的仿真[J]. 东北大学学报,2006,27(10):1067～1070
[5]李天平,李德瑾. 焦炉炼焦加热过程控制最优化系统综述[J].山东冶金,1992,21(5):10～14
[6]Yasuo Niva, Yoshiaki Watanabe, Mamoru Inaba.Upgrading of computerized combus- tion control in coke oven[C]. Ironmaking Conference Proceedings, 1989, 72: 421～425
[7]Shizuki kazaoka.The outomatic combustion control system for coke oven battery[C].Ironmaking Conference Proceedings,1981,64:181～187
[8]T Vander, A L Van Ballegooie, R A Vos.Automatic heat input control system for coke batteries[C]. Ironmaking Conference Proceedings,1990,73:127～133
[9]Jukka Swanijung,Petri Palmu. Development of coke-oven battery process manag- ement system at Rautaruukki Steelworks[J]. Iron and Steel Engineer,1996,73(2):46～49
[10]刘建岚,顾维忠,刘静康.焦炉加热计算机控制的工艺基础研究[J].炼焦化学,1984,18:264～269
[11]邬显青.美国凯塞公司焦炉加热系统(COHC)[J].燃料与化工,1989,20(5):11～15
[12]黄奇帆,汪元康,顾维忠.焦炉加热微型机最优控制系统[J].炼焦化学,1984 ,18:270～275
[13]Akikazu Nakazaki,Taiyo Matsuo,Yoji Nakagawa.Application and effects of automatic control of coke oven[C].Ironmaking Conference Proceedings, 1987, 70: 299～306
[14]NJW Thijssen,T Vander.Influences of the measured coke end temperature on coke battery heating[C].Ironmaking Conference Proceedings, 1984, 67: 209～214
[15]C Barbier.Automatic control of heating by “CRAPO” system in the coke ovenplantatSolmer[C].Ironmaking Conference Proceedings,1983,66:261～268
[16]H Tanaka, M Yasuno, H Oshinma.Application of fuzzy inference to combustion control for coke oven[C].Ironmaking Conference Proceedings, 1992, 75:509～513
[17]程长锋,周易.焦炉燃烧温度控制系统[J].冶金自动化,1993,(3):24～27
[18]侯勇严,孙瑜,郭文强.一种自适应模糊PID控制器的仿真研究[J].陕西科技大学学报 ,2004,22(2):48～53
[19]Akikazu Nakazaki,Taiyo Matsuo,Yoji Nakagawa.Application and effects of automatic control of coke oven[C]. Ironmaking Conference Proceedings, 1987, 70:299～306
[20]支晓明.宝钢 5、6 号焦炉加热自动控制系统[J].燃料与化工,2001,32(5):233～238
[21]姜玉山,严文福,王育红等.焦炉加热优化串级控制方案的研究与应用[J].山东冶金,2005,27(2):25～27
[22]姜政权.宝钢三期炼焦新技术[J].宝钢技术,1997,(1):19～20
[23]N J W Thijssen,T Vander.Influences of the measured coke end temperature on coke battery heating [C]. Ironmaking Conference Proceedings, 1984, 67: 209-214
[24]D J Hereda.Republic Steel’s application of computerized combustion control at the Warren coke battery[C]. Ironmaking Conference Proceedings, 1984, 67:197～204
[25]P V Hollo,J Verfaille,R Munnix 著.希德马焦化厂德加热和过程控制.卢树忠译.第二届国际焦化会议论文集.北京:冶金工业出版社,1992,294～299
[26]陈东,温治,霍芳等.焦炉直行温度和火落时间双反馈控制策略[J].燃料与化工,2003,(7):182～185
[27]王学武,顾幸生.焦炉加热过程智能控制综述[J].自动化仪表,2005,26(2):1～5
[28]Chunhua Yang,Min Wu,DeyaoShen,Geert Deconinck.Hybridi ntelligent control of gas collectors of coke ovens[J].Control Engineering Practice, 2001,47(9):725～733
[29]刘金琨.先进PID控制及其MATLAB仿真[M].北京:电子工业出版社,2003
[30]K.I.Choi.A mathematical model for the estimation of flue temperature in a coke oven[A],Ironmaking Conference Proceedings[C].Chicago,1997,56(1):107～113
[31]鲍立威,何敏,申志强.大型焦炉计算机优化控制系统[J].冶金自动化,1994,18(1):21～25
[32]陈希.基于人工神经网络的窑炉炉温控制的优化[J].自动化与仪表,1998,13(4):35～37
[33]E T Battel, K L Chen.Automatic coke oven heatings control system at Burn Harbor Works for normal and repair operation[C]. Ironmaking Conference Proceedings,1997, 80:499～504
[34]宁方青,姚昭章.多模式模糊控制技术在焦炉加热控制中的应用[J].自动化与仪表,1999,14(4): 37～40
[35]蔡晓燕.神经网络与PID复合算法的研究在焦炉温度控制中的应用[D].东北大学硕士论文,2006
[36]高军伟,叶阳东,史天运等.焦炉加热智能控制系统的研究与应用[J].信息与控制,2003,32(1):86～91
[37]古述波,陈云云,徐朝军等.广义预测控制算法在 JN43 型焦炉立火道温控中的应用[J].安徽工业大学学报,2004,21(4):291～294
[38]赵亚平.模糊免疫PID算法在焦炉温度控制中的研究[D].东北大学硕士论文,2006
[39]郑明东, 宁方青.焦炉立火道温度控制研究[J].大连理工大学学报,2001,41(4):442～445
[40]徐邦学.焦炉生产新工艺、新技术与焦炭质量分析测试实用手册[M].吉林:吉林音响出版社,2003
[41]高宪文,蔡晓燕.基于PID控制的遗传神经网络在焦炉温度控制中的应用研究[J].信息与控制,2005,34(6):709～713
[42]高宪文,赵亚平.模糊自适应PID在焦炉温度控制中的仿真[J].东北大学学报,2006,27(10):1067～1070
[43]Euntai Kim. A new approach to numerical stability analysis of fuzzy control ystems[J].IEEE Transactions on systems,2001,31(1):107～113
[44] Zhi-Wei Woo, Huang-Yuan Chung, Jin-Jye Lin. A PID type fuzzy controller with self-tuning scaling factors[J].Fuzzy set and system,2000,115(2):321～326
[45]Maeda M, Assilian S. A self-tuning fuzzy controller[J]. Fuzzy Sets and Systems, 1992,51(1):29～40
[46]严文福,郑明东,宁芳青等.焦炉加热优化串级控制的应用[J].燃料与化工,2004,35 (3):15～16
[47]郭齐胜,董志明,李亮等.系统建模与仿真(上册)[M]. 北京:国防工业出版社,2007
[48]雷琪,吴敏,曹卫华等.焦炉立火道温度的智能集成软测量方法及其应用[J]. 华东理工大学学报,2006,32(7):762～766
[49]Qiao W Z, Mizumoto M. PID type fuzzy controller and parameters adaptive method [J].Fuzzy sets and systems,1996,78(1):23～35
[50]易德生,郭萍.灰色理论与方法[M].北京:石油工业出版社,1992
[51]数理统计组编.数理统计[M].西安:西北工业大学出版社,2004
[52]黄长艺,严普强.机械工程测试技术基础[M].北京:机械工业出版社,2005
[53]李言俊,张科.系统辨识理论及应用[M].北京:国防工业出版社,2003
[54]Tanaka H, Yasuno M, Oshima Hetal. Application of fuzzy inference to combustioncontrol for coke oven(A), Ironmaking Conference proceedings[C].Toronto, 1992,52(7) :509～513
[55]Tan S H ,Yu Y Adaptive fuzzy modeling of nonlinear dynamical systems[J].Auto-ma Ta 1996,32(4):637～643
[56]Tarakanov A, Dasgupta D.A formal model of an artificial immune system [J].BiosyBiosystems, 2000,55(9):15～18
[57]Sergei Gutnikov, Yuri Melnikov. A simple non-linear model of immune response [J].Chaos, Solitonsand Fractals.2003,16(7):125～132
[58]Kangling Fang, Zhongjie Shen. A neural-fuzzy control in resistance fumace [J].IEEE international conference on intelligent processing systems,1997,51(6):200～204
[59]李英顺,伦淑娴,皮红梅.基于模糊神经网络的PID温度控制系统[J].鞍山钢铁学院学报,2002,25(6):408～412
[60]鲍可进.PID 参数自整定的温度控制[J].江苏理工大学学报,1995, 15(6):74
[61]陈友文.酒钢3#焦炉前馈反馈加热控制[J].系统与装置,1999, 21(3):16～19
[62]李春华,郭明良,岳云涛等.模糊控制在焦炉温度控制系统中的应用[J].黑龙江矿业学院学报,1998,8(2):26～29
[63]薛定宇,陈阳泉.基于MATLAB/Simulink的系统仿真技术与应用[M].北京:清华大学出版社,2002,192～249
[64]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005
[65]韩金旭,周宝昌,于宝川等.模糊控制在焦炉自动控制系统上的应用[J].制造业自动化,2004,26(7):62～65
[66]杨叔子,吴雅,轩建平.时间序列分析的工程应用[M].武汉:华中科技大学出版社,2007
[67]王沫然.MATLAB 与科学计算[M].北京:电子工业出版社,2005
[2]吴敏,刘永霞,曹卫华等.焦炉加热燃烧过程智能优化控制系统的研究及应用(上)[J].冶金自动化 ,2006,(5):25～28
[3]姚昭章.炼焦学[M].北京:冶金工业出版社,1995
[4]高宪文,赵亚平.模糊自适应PID在焦炉温度控制中的仿真[J]. 东北大学学报,2006,27(10):1067～1070
[5]李天平,李德瑾. 焦炉炼焦加热过程控制最优化系统综述[J].山东冶金,1992,21(5):10～14
[6]Yasuo Niva, Yoshiaki Watanabe, Mamoru Inaba.Upgrading of computerized combus- tion control in coke oven[C]. Ironmaking Conference Proceedings, 1989, 72: 421～425
[7]Shizuki kazaoka.The outomatic combustion control system for coke oven battery[C].Ironmaking Conference Proceedings,1981,64:181～187
[8]T Vander, A L Van Ballegooie, R A Vos.Automatic heat input control system for coke batteries[C]. Ironmaking Conference Proceedings,1990,73:127～133
[9]Jukka Swanijung,Petri Palmu. Development of coke-oven battery process manag- ement system at Rautaruukki Steelworks[J]. Iron and Steel Engineer,1996,73(2):46～49
[10]刘建岚,顾维忠,刘静康.焦炉加热计算机控制的工艺基础研究[J].炼焦化学,1984,18:264～269
[11]邬显青.美国凯塞公司焦炉加热系统(COHC)[J].燃料与化工,1989,20(5):11～15
[12]黄奇帆,汪元康,顾维忠.焦炉加热微型机最优控制系统[J].炼焦化学,1984 ,18:270～275
[13]Akikazu Nakazaki,Taiyo Matsuo,Yoji Nakagawa.Application and effects of automatic control of coke oven[C].Ironmaking Conference Proceedings, 1987, 70: 299～306
[14]NJW Thijssen,T Vander.Influences of the measured coke end temperature on coke battery heating[C].Ironmaking Conference Proceedings, 1984, 67: 209～214
[15]C Barbier.Automatic control of heating by “CRAPO” system in the coke ovenplantatSolmer[C].Ironmaking Conference Proceedings,1983,66:261～268
[16]H Tanaka, M Yasuno, H Oshinma.Application of fuzzy inference to combustion control for coke oven[C].Ironmaking Conference Proceedings, 1992, 75:509～513
[17]程长锋,周易.焦炉燃烧温度控制系统[J].冶金自动化,1993,(3):24～27
[18]侯勇严,孙瑜,郭文强.一种自适应模糊PID控制器的仿真研究[J].陕西科技大学学报 ,2004,22(2):48～53
[19]Akikazu Nakazaki,Taiyo Matsuo,Yoji Nakagawa.Application and effects of automatic control of coke oven[C]. Ironmaking Conference Proceedings, 1987, 70:299～306
[20]支晓明.宝钢 5、6 号焦炉加热自动控制系统[J].燃料与化工,2001,32(5):233～238
[21]姜玉山,严文福,王育红等.焦炉加热优化串级控制方案的研究与应用[J].山东冶金,2005,27(2):25～27
[22]姜政权.宝钢三期炼焦新技术[J].宝钢技术,1997,(1):19～20
[23]N J W Thijssen,T Vander.Influences of the measured coke end temperature on coke battery heating [C]. Ironmaking Conference Proceedings, 1984, 67: 209-214
[24]D J Hereda.Republic Steel’s application of computerized combustion control at the Warren coke battery[C]. Ironmaking Conference Proceedings, 1984, 67:197～204
[25]P V Hollo,J Verfaille,R Munnix 著.希德马焦化厂德加热和过程控制.卢树忠译.第二届国际焦化会议论文集.北京:冶金工业出版社,1992,294～299
[26]陈东,温治,霍芳等.焦炉直行温度和火落时间双反馈控制策略[J].燃料与化工,2003,(7):182～185
[27]王学武,顾幸生.焦炉加热过程智能控制综述[J].自动化仪表,2005,26(2):1～5
[28]Chunhua Yang,Min Wu,DeyaoShen,Geert Deconinck.Hybridi ntelligent control of gas collectors of coke ovens[J].Control Engineering Practice, 2001,47(9):725～733
[29]刘金琨.先进PID控制及其MATLAB仿真[M].北京:电子工业出版社,2003
[30]K.I.Choi.A mathematical model for the estimation of flue temperature in a coke oven[A],Ironmaking Conference Proceedings[C].Chicago,1997,56(1):107～113
[31]鲍立威,何敏,申志强.大型焦炉计算机优化控制系统[J].冶金自动化,1994,18(1):21～25
[32]陈希.基于人工神经网络的窑炉炉温控制的优化[J].自动化与仪表,1998,13(4):35～37
[33]E T Battel, K L Chen.Automatic coke oven heatings control system at Burn Harbor Works for normal and repair operation[C]. Ironmaking Conference Proceedings,1997, 80:499～504
[34]宁方青,姚昭章.多模式模糊控制技术在焦炉加热控制中的应用[J].自动化与仪表,1999,14(4): 37～40
[35]蔡晓燕.神经网络与PID复合算法的研究在焦炉温度控制中的应用[D].东北大学硕士论文,2006
[36]高军伟,叶阳东,史天运等.焦炉加热智能控制系统的研究与应用[J].信息与控制,2003,32(1):86～91
[37]古述波,陈云云,徐朝军等.广义预测控制算法在 JN43 型焦炉立火道温控中的应用[J].安徽工业大学学报,2004,21(4):291～294
[38]赵亚平.模糊免疫PID算法在焦炉温度控制中的研究[D].东北大学硕士论文,2006
[39]郑明东, 宁方青.焦炉立火道温度控制研究[J].大连理工大学学报,2001,41(4):442～445
[40]徐邦学.焦炉生产新工艺、新技术与焦炭质量分析测试实用手册[M].吉林:吉林音响出版社,2003
[41]高宪文,蔡晓燕.基于PID控制的遗传神经网络在焦炉温度控制中的应用研究[J].信息与控制,2005,34(6):709～713
[42]高宪文,赵亚平.模糊自适应PID在焦炉温度控制中的仿真[J].东北大学学报,2006,27(10):1067～1070
[43]Euntai Kim. A new approach to numerical stability analysis of fuzzy control ystems[J].IEEE Transactions on systems,2001,31(1):107～113
[44] Zhi-Wei Woo, Huang-Yuan Chung, Jin-Jye Lin. A PID type fuzzy controller with self-tuning scaling factors[J].Fuzzy set and system,2000,115(2):321～326
[45]Maeda M, Assilian S. A self-tuning fuzzy controller[J]. Fuzzy Sets and Systems, 1992,51(1):29～40
[46]严文福,郑明东,宁芳青等.焦炉加热优化串级控制的应用[J].燃料与化工,2004,35 (3):15～16
[47]郭齐胜,董志明,李亮等.系统建模与仿真(上册)[M]. 北京:国防工业出版社,2007
[48]雷琪,吴敏,曹卫华等.焦炉立火道温度的智能集成软测量方法及其应用[J]. 华东理工大学学报,2006,32(7):762～766
[49]Qiao W Z, Mizumoto M. PID type fuzzy controller and parameters adaptive method [J].Fuzzy sets and systems,1996,78(1):23～35
[50]易德生,郭萍.灰色理论与方法[M].北京:石油工业出版社,1992
[51]数理统计组编.数理统计[M].西安:西北工业大学出版社,2004
[52]黄长艺,严普强.机械工程测试技术基础[M].北京:机械工业出版社,2005
[53]李言俊,张科.系统辨识理论及应用[M].北京:国防工业出版社,2003
[54]Tanaka H, Yasuno M, Oshima Hetal. Application of fuzzy inference to combustioncontrol for coke oven(A), Ironmaking Conference proceedings[C].Toronto, 1992,52(7) :509～513
[55]Tan S H ,Yu Y Adaptive fuzzy modeling of nonlinear dynamical systems[J].Auto-ma Ta 1996,32(4):637～643
[56]Tarakanov A, Dasgupta D.A formal model of an artificial immune system [J].BiosyBiosystems, 2000,55(9):15～18
[57]Sergei Gutnikov, Yuri Melnikov. A simple non-linear model of immune response [J].Chaos, Solitonsand Fractals.2003,16(7):125～132
[58]Kangling Fang, Zhongjie Shen. A neural-fuzzy control in resistance fumace [J].IEEE international conference on intelligent processing systems,1997,51(6):200～204
[59]李英顺,伦淑娴,皮红梅.基于模糊神经网络的PID温度控制系统[J].鞍山钢铁学院学报,2002,25(6):408～412
[60]鲍可进.PID 参数自整定的温度控制[J].江苏理工大学学报,1995, 15(6):74
[61]陈友文.酒钢3#焦炉前馈反馈加热控制[J].系统与装置,1999, 21(3):16～19
[62]李春华,郭明良,岳云涛等.模糊控制在焦炉温度控制系统中的应用[J].黑龙江矿业学院学报,1998,8(2):26～29
[63]薛定宇,陈阳泉.基于MATLAB/Simulink的系统仿真技术与应用[M].北京:清华大学出版社,2002,192～249
[64]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005
[65]韩金旭,周宝昌,于宝川等.模糊控制在焦炉自动控制系统上的应用[J].制造业自动化,2004,26(7):62～65
[66]杨叔子,吴雅,轩建平.时间序列分析的工程应用[M].武汉:华中科技大学出版社,2007
[67]王沫然.MATLAB 与科学计算[M].北京:电子工业出版社,2005