精炼炉底吹氩智能控制系统的研究
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摘要
本文介绍了LF精炼炉底吹氩过程控制系统的工作原理、工艺要求、建模过程、控制策略以及控制系统的实现。通过对精炼炉底吹氩过程控制系统进行研究与分析，并根据流体力学的有关知识以及有关数据(其中包括设计数据、试验数据和运行数据)，建立起了被控对象的平均神经网络模型和执行机构(即PWM调压器和PCM调流器)的数学模型。在此模型的基础上，从底吹氩工艺要求和控制系统的实际情况出发，提出了压差内环模糊参数自适应PID控制策略和流量外环模糊PI复合控制策略，以实现氩气流量的精确控制。通过仿真结果可知，本文所采用的控制策略与常规的PID控制相比，具有较强的鲁棒性和良好的动态性能。最后，本文从控制系统实现的角度，分别阐述了该控制系统硬件和软件的设计与调试，并且给出了该控制系统在工业现场运行的结果。
This thesis introduces the working principle ,craftwork requirement ,modeling process ,control strategies and the realization of LF refining furnance bottom blowing Argon control system.Through the study and analysis of bottom blowing Argon process control system ,the thesis discusses the mean neural network model of controlled object and the mathematical models of the exectors ,PWM adjustable pressure controller and PCM adjustable flux controller according to the relevant liquid knowledge and relevant data ,including design data,test data and running data.To begin with the craftwork reguirement of bottom blowing Argon and the actual instance of the control system,it presents the strategies of fuzzy parameters self-adaptive PID control used in pressure difference inner loop and fuzzy plus PI compound control used in flux outer loop which are based on the above modeling in order to carry out the accurate control of Argon flux. Compared with normal PID, we can draw a conclusion that the control strategies have stronger robust performance and better dynamic performance from simulating results.Finally ,with the respect of the control system realization the thesis not only shows the design and debugging of the control system's hardware and software respectively but also gives the results of the control system under the industrial condition.
This thesis introduces the working principle ,craftwork requirement ,modeling process ,control strategies and the realization of LF refining furnance bottom blowing Argon control system.Through the study and analysis of bottom blowing Argon process control system ,the thesis discusses the mean neural network model of controlled object and the mathematical models of the exectors ,PWM adjustable pressure controller and PCM adjustable flux controller according to the relevant liquid knowledge and relevant data ,including design data,test data and running data.To begin with the craftwork reguirement of bottom blowing Argon and the actual instance of the control system,it presents the strategies of fuzzy parameters self-adaptive PID control used in pressure difference inner loop and fuzzy plus PI compound control used in flux outer loop which are based on the above modeling in order to carry out the accurate control of Argon flux. Compared with normal PID, we can draw a conclusion that the control strategies have stronger robust performance and better dynamic performance from simulating results.Finally ,with the respect of the control system realization the thesis not only shows the design and debugging of the control system's hardware and software respectively but also gives the results of the control system under the industrial condition.
引文
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[2] 伍先昭．钢包底吹试验．湖南冶金．1999(7)
[3] 蒋国昌等编著．纯净钢及二次精炼．上海科技出版社．1996
[4] 王占林编．近代液压控制．机械工业出版社．1997
[5] 金以慧主编．过程控制．清华大学出版社．1995．2
[6] 李树江、高宪文、柴天佑．模糊串级控制及其在精炼炉吹氩系统中应用．信息与控制．1998(2)
[7] 孙增圻等编著．智能控制理论与技术．清华大学出版社．1997
[8] 方崇智等编．过程仿真．清华大学出版社．1994
[9] 侯廷久、刘茂榆译．简明流体力学．中国建筑工业出版社．1985
[10] 于海生．微型计算机控制技术．清华大学出版社．1999
[11] 李少远、席裕庚等．智能控制的新进展(Ⅰ)．控制与决策．2000(1)
[12] 李少远、席裕庚等．智能控制的新进展(Ⅱ)．控制与决策．2000(3)
[13] 李军．武钢第二炼钢厂转炉底吹控制系统．冶金自动化．1999(1)
[14] 孙彦广等．智能钢包精炼炉控制系统．冶金自动化．1999(6)
[15] 贺尚红等．管道流体的瞬态仿真模型．中南工业大学学报．2000(4)
[16] 付萍等．基于智能的气压分级控制系统．系统工程与电子技术．2000(6)
[17] 陶永华、尹怡欣、葛芦生编著．新型PID控制及其应用．机械工业出版社．1999．5
[18] 李士勇编著．模糊控制·神经网络和智能控制论．哈尔滨工业大学出版社．1998．9
[19] 侯志林主编．过程控制与自动化仪表．机械工业出版社．2000．1
[20] 张乃尧，阎平凡编著．神经网络与模糊控制．清华大学出版社．1999．5
[21] 林锦国主编．过程控制系统·仪表·装置．东南大学出版社．2001．3
[22] 邵裕森、巴筱云主编．过程控制系统及仪表．机械工业出版社．1994．5
[23] 王树青等编著．先进控制技术及应用．化学工业出版社．2001．7
[24] 焦李成编著．神经网络的应用与实现．西安电子科技大学出版社．1995．3
[25] 薛定宇著．控制系统计算机辅助设计—MATLAB语言及应用．清华大学出版社．1998．3
[26] 刘增良主编．模糊技术与应用选编(3)．北京航空航天大学出版社．1998．12
[27] 余永权、曾碧编著．单片机模糊逻辑控制．北京航空航天大学出版社．1995．7
[28] 闻新、周露、王丹力、熊晓英编著．MATLAB神经网络应用设计．科学出版社．2000．9
[29] 欧阳黎明编著．MATLAB控制系统设计．国防工业出版社．2001．1
[30] 张卫平、张英儒编著．现代电子电路原理与设计．原子能出版社．1997
[31] 尤昌德著．现代控制理论基础．电子工业出版社．1996．7
[32] 何立民编著．MCS—51系列单片机应用系统设计—系统配置与接口技术．北京航空航天大学出版社．1995．1
[33] 周航慈著．单片机应用程序设计技术．北京航空航天大学出版社．1992．8
[34] 薛钧义、姚燕南主编．微机控制系统及其应用．西安交通大学出版社．1994．6
[35] 薛钧义、张彦斌编．MCS—51／96单片微型计算机及其应用．西安交通大学出版社．1995．6
[36] 许宏、赵克定、许宏光等．PCM控制的流体固定节流式气液联控伺服系统的建模与仿真研究．机床与液压．2000(4)
[37] 苏薇．模糊PID的研究．工业仪表与自动化装置．2001(2)
[38] 李碧霞、高文芳等．大包底吹氩水模拟试验研究．炼钢．2001(2)
[39] 高泽平．钢水精炼吹氩搅拌机理的研究．湖南冶金．2000(7)
[40] 侯媛彬、樊重俊等．用于辨识建模中的神经网络．计算机应用研究．1997(2)
[41] 杨熔，李永华，苏义鑫．用神经网络建立非线性系统模型研究．控制理论与应用．1995(12)
[42] 黎晓刚、张焰、郭迎卿．神经网络辨识及控制研究．电气传动自动化．1999．2
[43] 杨志龙．系统辨识理论与BP算法数学原理．兵工自动化．1998(4)
[44] 李英龙、吴大宏．采用平均技术的神经网络预测建模方法及其矿业应用．矿冶工程．2000(9)
[45] 皮衣霞、刘明伟．自控数—模节流控制及应用的研究．机械科学与技术．1999(11)
[46] 王鸣．一种模糊自整定PID参数控制器的设计与仿真．安徽机电学院学报．1999(6)
[47] 师黎、丁海．PID控制的参数模糊自整定方法．郑州工业大学学报．2001(9)
[48] 罗海福、毛义梅、张晶．一种参数自适应模糊PID控制器的设计与仿真．自动化与仪器仪表．2001(3)
[49] 刘喜梅、于飞、江蜀华．非线性动态系统建模的神经网络方法．青岛化工学院学报．2000(3)
[50] 王宣银．PCM气动伺服系统的建模研究．机床与液压．1998(5)
[51] 董秀林、周福章、史维祥．流体控制技术的发展和展望．洛阳工学院学报．1997(9)
[52] 符欲梅、唐中一、汪永超．PWM气动减压阀数学模型的建立、仿真及实验研究．液压气动与密封．1998(1)
[53] 金以慧等．过程控制的发展与展望．控制理论与应用．1997(2)
[54] 马竹梧．国外钢铁工业自动化的进展及展望．冶金自动化．1997(1)，(2)
[55] Schei T S. Automatic tuning of PID controllers based on transfer function estimation. Automatica, 1994,30 (12): 1983—1989
[56] Lee C C. Fuzzy logic in control systems:Fuzzy logic controller-Part &. IEEE Trans on SMC, 1990,20(2):404—435
[57] Buckley JJ. Sugeno type controllers are universal controllers. Fuzzy Sets and Systems, 1993, 53:299—303
[58] Buckley JJ. Universal fuzzy controllers. Automatica, 1992,28(6):1245—1248
[59] Wang L X. Stable adaptive fuzzy control of nonlinear systems. IEEE Trans on Fuzzy Systems, 1993,1(2):146—155
[60] Su C Y. Adaptive control of a class of nonlinear systems with fuzzy logic.IEEE Trans on Fuzzy Systems, 1994, 2(4):285—294
[61] Cao S G, N W Rees, G Feng. Stability analysis of fuzzy control systems. IEEE
Trans on SMC_Part B.1996, 2 6(1) :201-204
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