四辊轧机辊缝控制系统液压变参数问题的研究
|
摘要
厚度与板形精度是板带产品的两大质量指标。目前随着轧制理论、控制理论和人工智能理论的发展,以及它们在轧制过程中的应用,使得板带产品的厚度精度与板形指标有了很大提高,然而,对单个机架轧机采用专门的控制技术,实现微米级带材精度的控制,仍是目前板厚控制领域研究的热点问题之一。
板带轧机的控制非常复杂,其负载力大、扰动因素多、扰动关系复杂但同时对控制精度和响应速度要求很高,轧制过程是一个复杂的多变量强耦合非线性过程,各变量之间相互作用和影响密切。由于工况的改变,液压缸行程发生改变,使系统刚度及阻尼等参数发生变化,使系统在全工况范围内不能保持基本一致的响应时间和较高的控制精度。
本文以武钢1700mm五机架冷连轧机机组的第一机架液压AGC作为研究对象,对液压变参数的范围、影响和补偿控制进行了研究,具体工作可归纳为以下几个方面:
(1)概述了自动厚度控制的基本理论和变刚度AGC的控制策略,分析了该轧机应用的传统AGC的控制原理。
(2)根据实际的物理模型,建立了液压APC模型和传统的前馈及监控AGC数学模型,并给出了系统的主要参数。
(3)在建立的仿真模型的基础上利用基于MATLAB的Simulink工具箱进行了数字仿真,讨论了AGC系统中电液伺服阀固有频率、液压缸行程和负载阻尼等参数变化时系统的特征及其对系统控制精度与稳定性的影响,通过仿真值与实测值的对比验证了所建模型的正确性。
(4)针对变参数系统的刚度变化和阻尼比相对较小的问题,在满足系统全工况范围内上升时间趋于一致的目标下,提出了应用滞后校正和位移微分正反馈校正的综合校正措施。进而通过仿真分析得出了经过校正后的系统具有更高的控制精度的结论。本文针对APC系统具有参数变化的特点,探讨了液压APC系统参数的变化对厚度控制精度的影响,在保证系统在全工况范围内响应时间基本一致的前提下,采用了滞后校正和位移微分正反馈校正的综合校正措施,为现场轧制提供了一种新的解决方案。
The accuracy of strip gauge and the strip flatness are the main quality targets of a strip product. Currently, there have been huge advancements in the two targets above with the development of rolling theory, control theory, and artificial intelligence theory and their application in the rolling process. However, the application of the special control technology in singular-stand rolling mill and the realization of the control process with micron-level precision is still one of the hot spots in the control of strip thickness.
The control of the strip rolling mill is very complex because there exist heavy loads and all kinds of disturbances and complicated relationships between them, and meanwhile high control accuracies and instant response are required. The whole rolling process is a nonlinear one with multiple variables, strong couplings and close relationships and interactions between those variables. Owing to the change in the operating range, the corresponding change in the stroke of the hydraulic cylinder, such parameters as the system stiffness and damping ratio vary a deal, and as a result of the entire system is unable to maintain the basically consistent response time and unable to achieve a higher control precision within the whole operating range as well.
The paper discusses the ranges, influences and compensations of the variable parameters in the Automatic Gauge Control (AGC) in the first stand at WSPC’s 1700-millimetre cold tandem mill. The works discussed in this paper are as follows.
(1) The basic theory of the AGC system and the control strategy of the AGC system with variable stiffness are summarized, and the control principles in the traditional AGC used in the rolling mill mentioned above are analyzed.
(2) Based on the physical model in actual system, the mathematic model of both the Hydraulic Automatic Position Control (HAPC) system and the traditional AGC system with feedforward and monitors are established, and the main parameters of the system are provided.
(3) Simulations are implemented subsequently with the SIMULINK Blockset in MATLAB based on the mathematic model already established. The natural frequencies in electro-hydraulic servo valve, the displacement of the actuators and the damping ratio are variable. The feature of the system with the variable parameters and their influences on the accuracies and stabilities in AGC are discussed. The simulation results and the measured results are compared to verify the validity of the model.
(4) In order to solve the problems of variable stiffness and relatively small damping ratio, a compensation combining phase lag with positive differential feedback of displacement was advanced with the target for a constant response time in the whole operating range. The simulations demonstrated that the system compensated has higher control precision.
This paper discusses the influences of the variable parameters on the accuracy of the gauge control in accordance with the characteristics in the variations of the parameter in the APC system. Aimed at the realization of a constant response time in the whole operating range, a compensation combining phase lag with positive differential feedback of displacement are utilized, which offers a new solution to actual rolling process.
板带轧机的控制非常复杂,其负载力大、扰动因素多、扰动关系复杂但同时对控制精度和响应速度要求很高,轧制过程是一个复杂的多变量强耦合非线性过程,各变量之间相互作用和影响密切。由于工况的改变,液压缸行程发生改变,使系统刚度及阻尼等参数发生变化,使系统在全工况范围内不能保持基本一致的响应时间和较高的控制精度。
本文以武钢1700mm五机架冷连轧机机组的第一机架液压AGC作为研究对象,对液压变参数的范围、影响和补偿控制进行了研究,具体工作可归纳为以下几个方面:
(1)概述了自动厚度控制的基本理论和变刚度AGC的控制策略,分析了该轧机应用的传统AGC的控制原理。
(2)根据实际的物理模型,建立了液压APC模型和传统的前馈及监控AGC数学模型,并给出了系统的主要参数。
(3)在建立的仿真模型的基础上利用基于MATLAB的Simulink工具箱进行了数字仿真,讨论了AGC系统中电液伺服阀固有频率、液压缸行程和负载阻尼等参数变化时系统的特征及其对系统控制精度与稳定性的影响,通过仿真值与实测值的对比验证了所建模型的正确性。
(4)针对变参数系统的刚度变化和阻尼比相对较小的问题,在满足系统全工况范围内上升时间趋于一致的目标下,提出了应用滞后校正和位移微分正反馈校正的综合校正措施。进而通过仿真分析得出了经过校正后的系统具有更高的控制精度的结论。本文针对APC系统具有参数变化的特点,探讨了液压APC系统参数的变化对厚度控制精度的影响,在保证系统在全工况范围内响应时间基本一致的前提下,采用了滞后校正和位移微分正反馈校正的综合校正措施,为现场轧制提供了一种新的解决方案。
The accuracy of strip gauge and the strip flatness are the main quality targets of a strip product. Currently, there have been huge advancements in the two targets above with the development of rolling theory, control theory, and artificial intelligence theory and their application in the rolling process. However, the application of the special control technology in singular-stand rolling mill and the realization of the control process with micron-level precision is still one of the hot spots in the control of strip thickness.
The control of the strip rolling mill is very complex because there exist heavy loads and all kinds of disturbances and complicated relationships between them, and meanwhile high control accuracies and instant response are required. The whole rolling process is a nonlinear one with multiple variables, strong couplings and close relationships and interactions between those variables. Owing to the change in the operating range, the corresponding change in the stroke of the hydraulic cylinder, such parameters as the system stiffness and damping ratio vary a deal, and as a result of the entire system is unable to maintain the basically consistent response time and unable to achieve a higher control precision within the whole operating range as well.
The paper discusses the ranges, influences and compensations of the variable parameters in the Automatic Gauge Control (AGC) in the first stand at WSPC’s 1700-millimetre cold tandem mill. The works discussed in this paper are as follows.
(1) The basic theory of the AGC system and the control strategy of the AGC system with variable stiffness are summarized, and the control principles in the traditional AGC used in the rolling mill mentioned above are analyzed.
(2) Based on the physical model in actual system, the mathematic model of both the Hydraulic Automatic Position Control (HAPC) system and the traditional AGC system with feedforward and monitors are established, and the main parameters of the system are provided.
(3) Simulations are implemented subsequently with the SIMULINK Blockset in MATLAB based on the mathematic model already established. The natural frequencies in electro-hydraulic servo valve, the displacement of the actuators and the damping ratio are variable. The feature of the system with the variable parameters and their influences on the accuracies and stabilities in AGC are discussed. The simulation results and the measured results are compared to verify the validity of the model.
(4) In order to solve the problems of variable stiffness and relatively small damping ratio, a compensation combining phase lag with positive differential feedback of displacement was advanced with the target for a constant response time in the whole operating range. The simulations demonstrated that the system compensated has higher control precision.
This paper discusses the influences of the variable parameters on the accuracy of the gauge control in accordance with the characteristics in the variations of the parameter in the APC system. Aimed at the realization of a constant response time in the whole operating range, a compensation combining phase lag with positive differential feedback of displacement are utilized, which offers a new solution to actual rolling process.
引文
[1] 娄雅斌. 三机架冷连轧机 AGC 系统的仿真研究[J]. 鞍钢技术, 1999,(3): 22-25.
[2] 黄荣. 四辊可逆轧机张力控制系统的研究[D]. 沈阳:东北大学.1998.
[3] 于秋林. 四辊轧机辊系弹性变形的理论与实验研究[D]. 齐齐哈尔:东北重型机械学院.1986.
[4] 刘建昌, 王贞祥, 王立平等. AGC 系统控制模型与结构的研究[J]. 钢铁, 1994, 29(4): 35-39.
[5] Yoshikazu M, Toshio I. Modernization of gauge control system at Sumitomo Wakayama 5 stand cold mill [J], Iron and Steel engineer.1999, 8: 46-50.
[6] 金晓宏. 大型阀门开度电液控制系统研究[J]. 武汉冶金科技大学学报. 1997.6, 211-216.
[7] Jin Xiaohong, Rong Zhijun. Research on the adaptive model for electro-hydraulic position servo system with the external disturbances. Proceedings of the Fourth International Symposium on Fluid Power Transmission Symposium on Fluid Power Transmission and Control (ISFP’ 2003), International Academic Publisher World Publishing Corporation, Beijing, 2003.3, 198-201.
[8] 白埃民. 试论实现高精度板形和厚度一体化控制的途径[J]. 轧钢, 2001 (1): 10-13.
[9] 张进之. 热连轧控制系统优化设计和最优控制[J]. 冶金工业自动化, 2000(6): 48-51.
[10] FFF-AGC交流文件, Force feed forward automatic gauge control system overview, 2000.8.
[11] 孙德庆等. 一种前馈AGC系统的设计与分析[J]. 系统工程与电子技术, 1997(3);201-204.
[12] 王立锋, 李正熙. 一种带钢热连轧机的动态离散模型[C]. 首届全国有色金属自动化技术与应用学术年会论文集, 2003年10月, 南昌.
[13] 戴晓龙. 神经网络板厚板形综合控制系统的研究[D]. 北京: 北京科技大学, 1995.
[14] Tezuka Tomoyuki, Yamashita Takashi. Application of a new automatic gauge control system for the tandem cold mill. Power and Industrial systems, IEEE Tansactions on Industrial Applications, 2002, 38(2):5 53-558.
[15]王秀梅. 人工神经网络和数学模型在热连轧机组轧制力预报中的综和应用[J]. 钢铁, 1999(3): 189-193.
[16] Yao-Yiaolan, Zhang-Disheng. Adaptive modification of the rolling force prediction[J]. Journal of Beijing Institute of Technology, 2002, 11(1):33-36.
[17] 张进之. 宝钢2050mm热连轧设定模型及自适应分析研究[J]. 钢铁. 2001(7): 49-95.
[18] 钟云峰, 谭树彬, 徐心和. 板带轧机 AGC 变刚度控制的研究[J]. 冶金设备 2006(1): 15-17.
[19] 张进之. 压力 AGC 分类及控制效果分析[J]. 钢铁研究总院学报.1988(6): 87-94.
[20] 赵毅德. 中厚板轧机液压 AGC 的工作原理[J]. 甘肃冶金, 1997(3): 11-21.
[21] 王君, 王国栋. 厚度机型变刚度控制系统的研究[J]. 轧钢, 2001(12): 126-128.
[22] 王君, 李建平, 王国栋. 压力闭环下的轧机变刚度控制[J]. 控制与决策, 2002(1): 126-128.
[23] 刘博. 轧机-机架 AGC 控制机理的研究[J]. 冶金设备, 2003(2): 35-38.
[24] 日本钢铁协会. 板带轧制理论与实践[M] .王国栋, 吴国良译. 北京: 中国铁道出版社, 1990.
[25] 张进之. 压力 AGC 系统参数方程及变刚度轧机分析[J] . 冶金自动化, 1984, 8(1): 24-31.
[26] 雷琴. 冷轧机辊缝控制的液压变刚度问题[D]. 武汉: 武汉科技大学, 2006.
[27] 王君, 牛文勇, 王国栋. 厚度计型和动态设定型变刚度系统的统一性证明[J]. 控制与决策.2001, 7: 16(4): 461-464.
[28] 王占林, 裘丽华. 非对称液压伺服系统的理论研究[J]. 机床与液压.1987(4): 7-9.
[29] 王占林, 裘丽华. 非对称液压伺服系统的特性补偿[J]. 机床与液压.1987(6): 1-7.
[30] 王宣银. 非对称液压缸系统压力跃变的研究[J]. 组合机床与自动化加工技术. 1996(11): 15-17.
[31] 孟繁华. 现代液压控制系统讲义. 哈工大动力工程系.1990.1.
[32] Meng Fanhua. Frequency Characteristic of an Electro-hydraulic Servomechanism With a Nonsymmetrical Cylinder. Report of Department of Mechanical Engineering, Sophia University, 1984.11.
[33] 李洪人. 液压控制系统[M]. 国防工业出版社. 1981:186-187, 191-199.
[34] Satoru Hayashi, Emeritus. Nonlinear phenomenon in hydraulic system[J]. Journal of Fluid control.1998, 18(4): 48-52.
[35] 卢长耿. 液压控制系统的分析与设计[J]. 煤炭工业出版社. 1991.
[36] 王栋梁, 李洪人. 非对称阀控制非对称缸的分析研究[J]. 山东建材学院学报. 2001 (6): 123-127.
[37] 关景泰, 王海滨, 周俊龙. 非对称阀控制非对称缸的动态分析[J]. 同济大学学报. 2001, (9):1130-1134.
[38] Bret R. Givens. An engineering design simulator for advanced distributed simulation. IEEE, 1996:565-571.
[39] M. R. Sirouspoun, S. E. Salcudean. Nonlinear control of a hydraulic parallel manipulator. Processing of the 2001 IEEE:3760-3765.
[40] 赵继云, 柴光远, 李熙照. 非对称阀控非对称缸的理论研究[J]. 中国矿业大学学报.1996(12): 22-27.
[41] 刘长年. 液压伺服系统优化设计理论[M]. 北京: 冶金工业出版社.1989: 105-127,155-160.
[42] 陈亚琛. 冷轧机液压AGC系统的控制模型与仿真研究[D]. 武汉: 武汉科技大学, 2004.
[43] 王春行. 液压伺服控制系统[M]. 北京: 机械工业出版社, 1989, 128-130.
[44] 王春行. 液压控制系统[M]. 北京: 机械工业出版社.2006.1: 70-71.
[45] 金以慧、方崇智. 过程控制[M] . 北京: 清华大学出版社, 1993.
[46] W K Ho, C C Hang, J H Zhou. Performance and gain and phase margins of well- known PI tuning formulas. IEEE Trans. Control Systems Technology, Vol.3, 245-248, 1995.
[47] WK Ho, O P Gan, E B Tay, E L Ang. Performance and gain and phase margins of well-known PID tuning formulas. IEEE Trans. Control Systems Technology, Vo1.4, No.4, 473-477, 1996.
[48] 刘建昌. 基于神经网络的自适应厚度控制[J] , 钢铁, 1999, 34(11): 33-36.
[49] 方一鸣, 焦晓红, 王益群. 极点配置自校正控制及其在冷带轧机厚控系统中的应用[J], 控制理论与应用, 2000, 1 7(2): 240-243.
[50] 潘学军, 柴天佑. 模糊控制在冷轧厚度控制中的应用[C], 中国控制与决策学术年会论文集, 1997, 563-566.
[51] 方一鸣, 焦晓红等. 自校正 PID 控制在冷连轧带钢厚控系统中的应用[J], 冶金自动化, 1999(4): 30-33.
[52] Sharma U., et al. Application of fuzzy logic technology to tandem mill transitional gauge variation[J], Iron and Steel Engineer, 1998, 7 5(6):40-43.
[53] Kim I. S. , et al. Subspace model identification and infinity servo control of tandem cold mill[J], Proceedings of the 1999 38th SICE Annual Conference, 1999: 951-920.
[54] Fan J, Tieu A K, Yuen D. Strip thickness control of mill using self-tuning PID neuron controller[J], ISIJ international,1999, 39(1): 39-46
[55] Frank F. Application of fuzzy logic technology to tandem mill transitional gauge variation[J], Iron and Steel Engineer, 1998, 6 : 40-43
[56] Rajani K, Nikhil R. A robust self-tuning scheme for PI-and PD-type fuzzy controllers[J], IEEE transactions on fuzzy systems, 1999, 7 (1): 2-15
[57] Sbarbaro D, et al. An artificial neural network for milling application[J], Steel Times,1995, 223(4):137-138.
[58]. Pichler R, Pfaffermayer M. On-line optimization of the rolling process-a case of neural networks[J], Steel Times, 1996,224(9):310-311.
[59] 周克敏、J.C.Doyle、K .Glover. 鲁棒与最优控制[M] . 北京: 国防工业出版社, 2002.
[60] H. E. Merritt. Hydraulic control systems[J]. John Wiley & Sons, c1967.
[61] R. H. Warring. Hydraulic handbook[M]. Trade and Technical Press Ltd, c1983.
[62] N. Niksefat, N. Sepehri. Design and experimental evaluation of a robust force controller for an electro-hydraulic actuator via quantitative feedback theory. Control Engineering Practice,8 (2000) 1335-1345.
[63] Knohl, H. Unbehauen. Adaptive position control of electro-hydraulic servo systems using ANN. Mechatronics 10 (2000) 127-143.
[64] Gene F. Franklin, J. David Powell and Michael Workman. Digital Control of Dynamic Systems[M]. 北京: 清华大学出版社, 2001, 360-420.
[65] 周晓宏, 刘红军, 武雅丽, 汤娟. 基于MATLAB的H∞鲁棒控制器设计[J]. 交通运输工程学报, 2002.9, 120-122.
[66] 付兴建, 童朝南. 冷连轧机液压系统的H∞混合灵敏度鲁棒控制器设计[J]. 液压与传动, 2005.5, 24-25.
[67] 袁明新, 侯志伟, 申焱. 电液位置伺服系统的最优控制设计[J]. 淮阳工学院学报, 2004.6, 16-19.
[68] 王幼民, 司妙丽. 电液位置伺服系统干扰抑止问题的H∞控制[J]. 农业机械学报, 2004.11, 164-170.
[69] E. John M. Geddes, Lan Ppstlethwaife. 利用多变量鲁棒控制技术提高冷连轧产品质量.世界钢铁[J], 2006.2, 5-11.
[70] M. R. Sirouspour and S. E. Salcudean. Robust Controller Design for Cancelling Biodynamil Feedthrough. IEE Proc.-control Theory Appl., Vol.142.No.5, September 1995.
[71] M. J. Grimble. Polynomial solution of the standard H∞ control problem for strip mill gauge control. IEE Proc.-control Theory Appl., Vol. 142. No.5, September 1995.
[72] 孙一康. 带钢冷连轧计算机控制[M]. 北京: 冶金工业出版社,2002.
[73] 连家创. 轧机基本理论进展[J]. 西安: 西安重型机械研究所. 1983.
[2] 黄荣. 四辊可逆轧机张力控制系统的研究[D]. 沈阳:东北大学.1998.
[3] 于秋林. 四辊轧机辊系弹性变形的理论与实验研究[D]. 齐齐哈尔:东北重型机械学院.1986.
[4] 刘建昌, 王贞祥, 王立平等. AGC 系统控制模型与结构的研究[J]. 钢铁, 1994, 29(4): 35-39.
[5] Yoshikazu M, Toshio I. Modernization of gauge control system at Sumitomo Wakayama 5 stand cold mill [J], Iron and Steel engineer.1999, 8: 46-50.
[6] 金晓宏. 大型阀门开度电液控制系统研究[J]. 武汉冶金科技大学学报. 1997.6, 211-216.
[7] Jin Xiaohong, Rong Zhijun. Research on the adaptive model for electro-hydraulic position servo system with the external disturbances. Proceedings of the Fourth International Symposium on Fluid Power Transmission Symposium on Fluid Power Transmission and Control (ISFP’ 2003), International Academic Publisher World Publishing Corporation, Beijing, 2003.3, 198-201.
[8] 白埃民. 试论实现高精度板形和厚度一体化控制的途径[J]. 轧钢, 2001 (1): 10-13.
[9] 张进之. 热连轧控制系统优化设计和最优控制[J]. 冶金工业自动化, 2000(6): 48-51.
[10] FFF-AGC交流文件, Force feed forward automatic gauge control system overview, 2000.8.
[11] 孙德庆等. 一种前馈AGC系统的设计与分析[J]. 系统工程与电子技术, 1997(3);201-204.
[12] 王立锋, 李正熙. 一种带钢热连轧机的动态离散模型[C]. 首届全国有色金属自动化技术与应用学术年会论文集, 2003年10月, 南昌.
[13] 戴晓龙. 神经网络板厚板形综合控制系统的研究[D]. 北京: 北京科技大学, 1995.
[14] Tezuka Tomoyuki, Yamashita Takashi. Application of a new automatic gauge control system for the tandem cold mill. Power and Industrial systems, IEEE Tansactions on Industrial Applications, 2002, 38(2):5 53-558.
[15]王秀梅. 人工神经网络和数学模型在热连轧机组轧制力预报中的综和应用[J]. 钢铁, 1999(3): 189-193.
[16] Yao-Yiaolan, Zhang-Disheng. Adaptive modification of the rolling force prediction[J]. Journal of Beijing Institute of Technology, 2002, 11(1):33-36.
[17] 张进之. 宝钢2050mm热连轧设定模型及自适应分析研究[J]. 钢铁. 2001(7): 49-95.
[18] 钟云峰, 谭树彬, 徐心和. 板带轧机 AGC 变刚度控制的研究[J]. 冶金设备 2006(1): 15-17.
[19] 张进之. 压力 AGC 分类及控制效果分析[J]. 钢铁研究总院学报.1988(6): 87-94.
[20] 赵毅德. 中厚板轧机液压 AGC 的工作原理[J]. 甘肃冶金, 1997(3): 11-21.
[21] 王君, 王国栋. 厚度机型变刚度控制系统的研究[J]. 轧钢, 2001(12): 126-128.
[22] 王君, 李建平, 王国栋. 压力闭环下的轧机变刚度控制[J]. 控制与决策, 2002(1): 126-128.
[23] 刘博. 轧机-机架 AGC 控制机理的研究[J]. 冶金设备, 2003(2): 35-38.
[24] 日本钢铁协会. 板带轧制理论与实践[M] .王国栋, 吴国良译. 北京: 中国铁道出版社, 1990.
[25] 张进之. 压力 AGC 系统参数方程及变刚度轧机分析[J] . 冶金自动化, 1984, 8(1): 24-31.
[26] 雷琴. 冷轧机辊缝控制的液压变刚度问题[D]. 武汉: 武汉科技大学, 2006.
[27] 王君, 牛文勇, 王国栋. 厚度计型和动态设定型变刚度系统的统一性证明[J]. 控制与决策.2001, 7: 16(4): 461-464.
[28] 王占林, 裘丽华. 非对称液压伺服系统的理论研究[J]. 机床与液压.1987(4): 7-9.
[29] 王占林, 裘丽华. 非对称液压伺服系统的特性补偿[J]. 机床与液压.1987(6): 1-7.
[30] 王宣银. 非对称液压缸系统压力跃变的研究[J]. 组合机床与自动化加工技术. 1996(11): 15-17.
[31] 孟繁华. 现代液压控制系统讲义. 哈工大动力工程系.1990.1.
[32] Meng Fanhua. Frequency Characteristic of an Electro-hydraulic Servomechanism With a Nonsymmetrical Cylinder. Report of Department of Mechanical Engineering, Sophia University, 1984.11.
[33] 李洪人. 液压控制系统[M]. 国防工业出版社. 1981:186-187, 191-199.
[34] Satoru Hayashi, Emeritus. Nonlinear phenomenon in hydraulic system[J]. Journal of Fluid control.1998, 18(4): 48-52.
[35] 卢长耿. 液压控制系统的分析与设计[J]. 煤炭工业出版社. 1991.
[36] 王栋梁, 李洪人. 非对称阀控制非对称缸的分析研究[J]. 山东建材学院学报. 2001 (6): 123-127.
[37] 关景泰, 王海滨, 周俊龙. 非对称阀控制非对称缸的动态分析[J]. 同济大学学报. 2001, (9):1130-1134.
[38] Bret R. Givens. An engineering design simulator for advanced distributed simulation. IEEE, 1996:565-571.
[39] M. R. Sirouspoun, S. E. Salcudean. Nonlinear control of a hydraulic parallel manipulator. Processing of the 2001 IEEE:3760-3765.
[40] 赵继云, 柴光远, 李熙照. 非对称阀控非对称缸的理论研究[J]. 中国矿业大学学报.1996(12): 22-27.
[41] 刘长年. 液压伺服系统优化设计理论[M]. 北京: 冶金工业出版社.1989: 105-127,155-160.
[42] 陈亚琛. 冷轧机液压AGC系统的控制模型与仿真研究[D]. 武汉: 武汉科技大学, 2004.
[43] 王春行. 液压伺服控制系统[M]. 北京: 机械工业出版社, 1989, 128-130.
[44] 王春行. 液压控制系统[M]. 北京: 机械工业出版社.2006.1: 70-71.
[45] 金以慧、方崇智. 过程控制[M] . 北京: 清华大学出版社, 1993.
[46] W K Ho, C C Hang, J H Zhou. Performance and gain and phase margins of well- known PI tuning formulas. IEEE Trans. Control Systems Technology, Vol.3, 245-248, 1995.
[47] WK Ho, O P Gan, E B Tay, E L Ang. Performance and gain and phase margins of well-known PID tuning formulas. IEEE Trans. Control Systems Technology, Vo1.4, No.4, 473-477, 1996.
[48] 刘建昌. 基于神经网络的自适应厚度控制[J] , 钢铁, 1999, 34(11): 33-36.
[49] 方一鸣, 焦晓红, 王益群. 极点配置自校正控制及其在冷带轧机厚控系统中的应用[J], 控制理论与应用, 2000, 1 7(2): 240-243.
[50] 潘学军, 柴天佑. 模糊控制在冷轧厚度控制中的应用[C], 中国控制与决策学术年会论文集, 1997, 563-566.
[51] 方一鸣, 焦晓红等. 自校正 PID 控制在冷连轧带钢厚控系统中的应用[J], 冶金自动化, 1999(4): 30-33.
[52] Sharma U., et al. Application of fuzzy logic technology to tandem mill transitional gauge variation[J], Iron and Steel Engineer, 1998, 7 5(6):40-43.
[53] Kim I. S. , et al. Subspace model identification and infinity servo control of tandem cold mill[J], Proceedings of the 1999 38th SICE Annual Conference, 1999: 951-920.
[54] Fan J, Tieu A K, Yuen D. Strip thickness control of mill using self-tuning PID neuron controller[J], ISIJ international,1999, 39(1): 39-46
[55] Frank F. Application of fuzzy logic technology to tandem mill transitional gauge variation[J], Iron and Steel Engineer, 1998, 6 : 40-43
[56] Rajani K, Nikhil R. A robust self-tuning scheme for PI-and PD-type fuzzy controllers[J], IEEE transactions on fuzzy systems, 1999, 7 (1): 2-15
[57] Sbarbaro D, et al. An artificial neural network for milling application[J], Steel Times,1995, 223(4):137-138.
[58]. Pichler R, Pfaffermayer M. On-line optimization of the rolling process-a case of neural networks[J], Steel Times, 1996,224(9):310-311.
[59] 周克敏、J.C.Doyle、K .Glover. 鲁棒与最优控制[M] . 北京: 国防工业出版社, 2002.
[60] H. E. Merritt. Hydraulic control systems[J]. John Wiley & Sons, c1967.
[61] R. H. Warring. Hydraulic handbook[M]. Trade and Technical Press Ltd, c1983.
[62] N. Niksefat, N. Sepehri. Design and experimental evaluation of a robust force controller for an electro-hydraulic actuator via quantitative feedback theory. Control Engineering Practice,8 (2000) 1335-1345.
[63] Knohl, H. Unbehauen. Adaptive position control of electro-hydraulic servo systems using ANN. Mechatronics 10 (2000) 127-143.
[64] Gene F. Franklin, J. David Powell and Michael Workman. Digital Control of Dynamic Systems[M]. 北京: 清华大学出版社, 2001, 360-420.
[65] 周晓宏, 刘红军, 武雅丽, 汤娟. 基于MATLAB的H∞鲁棒控制器设计[J]. 交通运输工程学报, 2002.9, 120-122.
[66] 付兴建, 童朝南. 冷连轧机液压系统的H∞混合灵敏度鲁棒控制器设计[J]. 液压与传动, 2005.5, 24-25.
[67] 袁明新, 侯志伟, 申焱. 电液位置伺服系统的最优控制设计[J]. 淮阳工学院学报, 2004.6, 16-19.
[68] 王幼民, 司妙丽. 电液位置伺服系统干扰抑止问题的H∞控制[J]. 农业机械学报, 2004.11, 164-170.
[69] E. John M. Geddes, Lan Ppstlethwaife. 利用多变量鲁棒控制技术提高冷连轧产品质量.世界钢铁[J], 2006.2, 5-11.
[70] M. R. Sirouspour and S. E. Salcudean. Robust Controller Design for Cancelling Biodynamil Feedthrough. IEE Proc.-control Theory Appl., Vol.142.No.5, September 1995.
[71] M. J. Grimble. Polynomial solution of the standard H∞ control problem for strip mill gauge control. IEE Proc.-control Theory Appl., Vol. 142. No.5, September 1995.
[72] 孙一康. 带钢冷连轧计算机控制[M]. 北京: 冶金工业出版社,2002.
[73] 连家创. 轧机基本理论进展[J]. 西安: 西安重型机械研究所. 1983.