粉状炸药生产线改性塔压力控制技术研究
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摘要
改性塔是改性粉状硝铵炸药生产线中对硝酸铵进行改性的装置,作为粉状炸药生产过程中的一个关键设备,其压力控制的好坏与否直接关系到炸药质量的高低,对整个系统的安全性具有极大的影响。因此,改性塔压力自动控制系统的研究与设计对于实现粉状炸药生产过程的全自动化、提高产品质量、降低劳动强度具有非常重要的意义。
本文系统介绍了粉状炸药的生产工艺,分析了改性塔压力的产生及其特点。在此基础上对改性塔压力系统进行机理建模得到模型结构,并通过测试建模法辨识出模型参数,得到了改性塔压力系统的近似模型。
改性塔压力系统具有时变性和滞后性的特点。本文分析了滞后环节的产生及其对系统性能的影响,详细介绍了Smith预估控制原理,着重研究了单神经元自适应PID控制器的设计以及对算法的改进。Smith预估控制是基于模型的补偿控制,但它对参数变化较为敏感。基于此,本文提出了一种单神经元自适应Smith预估补偿控制策略,将单神经元自适应PID作为Smith预估控制的主控制器,而将Smith预估器作为补偿器。利用MAILAB中的Simulink工具对控制器进行仿真,仿真结果表明,该控制方案具有良好的控制品质和鲁棒性。
本文最后介绍了改性塔压力控制系统的结构,同时进行了控制系统的软件设计。现场运行情况表明,所采用的控制器稳定可靠,实现了粉状炸药的连续化生产,提高了产品的产量和质量。
Reaction tower, which is one of the key units in the process of powdery explosive production, is used to modify the character of ammonium nitrate in the production line of powdery explosive. The pressure stability of the reaction tower influences not only the performance of the dynamite but also the security of its producing system. Therefore, the research and design for the automatic pressure control system of the reaction tower are of great significance for realizing the automatic control in the manufacture of powdery explosive, improving the quantity of product and decreasing working intensity.
Based on the analyses for the production process of the powdery explosive and the characteristic of the reaction tower-pressure system, a model structure of reaction tower-pressure control system is established firstly, and then the system parameters are identified by using classical step response method. An approximate system model is deduced at last.
The main characteristics of the reaction tower-pressure control system are time-delay and time-varying. The influence which time-delay loop brings to the system performance and the principle of the Smith predictor are introduced particularly in this paper. The theory of single neuron adaptive PID controller is researched, mainly in its algorithm and the algorithm modification. Smith predictor can effectively remove the time-delay from the closed-loop characteristic equation, but it is sensitive to the change of the parameters. In order to solve this problem, a strategy of single neuron self-adapting compensation control via Smith predictor is put forward. In this strategy, the single neuron PID is used as the main controller, while Smith predictor is used as the compensator. The intelligent controller is simulated with Simulink in Matlab and the results show that the proposed scheme has a good control character and strong robustness.
Finally the structure of the system is introduced and the software system is designed. The running results indicate the control system is stable and reliable. The continuous production is successfully realized. The quantity and quality of product are also improved.
本文系统介绍了粉状炸药的生产工艺,分析了改性塔压力的产生及其特点。在此基础上对改性塔压力系统进行机理建模得到模型结构,并通过测试建模法辨识出模型参数,得到了改性塔压力系统的近似模型。
改性塔压力系统具有时变性和滞后性的特点。本文分析了滞后环节的产生及其对系统性能的影响,详细介绍了Smith预估控制原理,着重研究了单神经元自适应PID控制器的设计以及对算法的改进。Smith预估控制是基于模型的补偿控制,但它对参数变化较为敏感。基于此,本文提出了一种单神经元自适应Smith预估补偿控制策略,将单神经元自适应PID作为Smith预估控制的主控制器,而将Smith预估器作为补偿器。利用MAILAB中的Simulink工具对控制器进行仿真,仿真结果表明,该控制方案具有良好的控制品质和鲁棒性。
本文最后介绍了改性塔压力控制系统的结构,同时进行了控制系统的软件设计。现场运行情况表明,所采用的控制器稳定可靠,实现了粉状炸药的连续化生产,提高了产品的产量和质量。
Reaction tower, which is one of the key units in the process of powdery explosive production, is used to modify the character of ammonium nitrate in the production line of powdery explosive. The pressure stability of the reaction tower influences not only the performance of the dynamite but also the security of its producing system. Therefore, the research and design for the automatic pressure control system of the reaction tower are of great significance for realizing the automatic control in the manufacture of powdery explosive, improving the quantity of product and decreasing working intensity.
Based on the analyses for the production process of the powdery explosive and the characteristic of the reaction tower-pressure system, a model structure of reaction tower-pressure control system is established firstly, and then the system parameters are identified by using classical step response method. An approximate system model is deduced at last.
The main characteristics of the reaction tower-pressure control system are time-delay and time-varying. The influence which time-delay loop brings to the system performance and the principle of the Smith predictor are introduced particularly in this paper. The theory of single neuron adaptive PID controller is researched, mainly in its algorithm and the algorithm modification. Smith predictor can effectively remove the time-delay from the closed-loop characteristic equation, but it is sensitive to the change of the parameters. In order to solve this problem, a strategy of single neuron self-adapting compensation control via Smith predictor is put forward. In this strategy, the single neuron PID is used as the main controller, while Smith predictor is used as the compensator. The intelligent controller is simulated with Simulink in Matlab and the results show that the proposed scheme has a good control character and strong robustness.
Finally the structure of the system is introduced and the software system is designed. The running results indicate the control system is stable and reliable. The continuous production is successfully realized. The quantity and quality of product are also improved.
引文
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[3]李成伟,刘忠法.PSC粉体表面改性机研制[J].非金属矿,2004,27(2):51-52
[4]吕春绪,刘祖亮,倪欧琪.工业炸药[M].北京:兵器工业出版社,1994
[5]肖国,刘厚平,郭子庭.浅析美日中工业炸药的发展近况[J].爆破器材,2003,32(3):14-19
[6]李国仲.日本工业炸药的发展过程与现状[J].工程爆破,1998,4(4):71-75
[7]刘厚平,肖国,郭子庭.粉状硝铵炸药的连续自动化生产及其生产本质安全性问题[J].矿冶工程,2003,23(3):4-5
[8]周向群.试论乳化炸药连续生产技术的发展[J].煤矿爆破,1997(4):19-21
[9]吕春绪.膨化硝铵炸药[M].北京:兵器工业出版社,2001
[10]Jill P.Card,Debbie L.Sniderman,Casimir Klimasauskas.Dynamic Neural Control for a Plasma Etch Process.IEEE Trans.on Neural Networks,1997,8(4):883-901
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[13]王福生,孟晓风.一种气体压力控制方法及应用[J].测控技术,2001,20(4):26-28
[14]Zhi-wei Woo,Hung-Yuan Chung,Jin-Jye Lin.A PID type fuzzy controller with self-tuning scaling factors.Fuzzy Sets and Systems,2000,115(2):321-326
[15]K.J.Hunt.Extending the Functional Equivalence of Radial Basis Function Networks and Fuzzy Inference Systems.IEEE Trans.on Neural Networks,1996,7(3):776-781
[16]Mohsen Razzaghi,Mehdi Razzaghi.Taylor series analysis of time-varying multi-delay systems.International Journal of Control,1989,50(1):183-192
[17]K.K.TAN,Q.G.WANG,T.H.LEE,and Q.BI.New approach to analysis and design of Smith-predictor controller.AICHE J,1996,42(6):1793-1797
[18]S.Majhi and D.P.Atherton.Modified Smith predictor and controller for processes with time delay.IEE Proceedings:Control Theory and Applications,1999,146(5):359-366
[19]李克升,叶涛,王强等.气流工艺生产2号岩石粉状铵梯油炸药可行性研究[J].爆破器材,1999,28(3):8-12
[20]陆褚明,吕春绪.几种粉状铵梯油炸药配方的分析与评价[J].含能材料,2001,9(2):94-96
[21]李仕洪,李建设,刘顺强.浅析工业炸药殉爆距离试验方法的改进[J].爆破器材.2005.34(3):20-24
[22]H.Omura.Introduction of PLC instrumentation and application example.Kami Pa Gikyoshi/Japan Tappi Journal,2006,60(3):85-92
[23]M.Namie.Application of PLC for PA and future evolution of PLC based process controller.Kami Pa Gikyoshi/Japan Tappi Journal,2006,60(3):37-43
[24]伍沅.化工过程动态[M].北京:化学工业出版社,1998
[25]方崇智,萧德云.过程辨识[M].北京:清华大学出版社,2003
[26]周春晖.化工过程控制原理[M].北京:化学工业出版社,1998
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[29]陈宗海.过程系统建模与仿真[M].合肥:中国科学技术大学出版社,1997
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[33]孙秀桂,陆绮荣,赵政春.大时滞控制系统的控制策略分析[J].安阳工学院学报,2006(3):4-7
[34]陶永华.PID控制原理和自整定策略[J].工业仪表与自动化装置,1997(4):60-64
[35]于海生.微型计算机控制技术[M].北京:清华大学出版社,1999
[36]O.J.Smith.Closer Control of loops with Dead time.Chemical Engineering Progress,1957,53(5):217-219
[37]顾伟军,彭亦功.智能控制技术及其应用[J].自动化仪表,2006(zl):101-104
[38]蔡自兴,徐光枯.人工智能及其应用[M].北京:清华大学出版社,1996
[39]张昌凡,何静.滑膜变结构的智能控制理论与应用研究[M].北京:科学出版社,2005
[40]王建义.智能自动化技术在汽车工程上的应用:[硕士学位论文].广州:广东工业大学,2005
[41]Qiang Sheng,Zhang Xianyi,Wang Changhong,Gao X.Z.,Liu Zilong.Design and implementation of an adaptive PID controller using single neuron learning algorithm.Proceedings of the 4th World Congress on Intelligent Control and Automation,June 10-14,Shanghai,China,Page(s):2279-2283
[42]徐英,徐用茂,杨尔辅.时变大纯滞后系统的单神经元预测控制[J].清华大学学报(自然科学版),2002,42(3):383-386
[43]郭前岗,舒怀林.一种新型神经网络结构PID控制器及其仿真研究[J].电气传动自动化,1999,21(2):29-32
[44]何继爱,黄智武,田亚菲.一种单神经元PID控制器[J].甘肃科学学报,2004,16(4):70-73
[45]刘玲,董海鹰.三容水箱的单神经元自适应PID控制研究[J].信息技术,2005(8):132-134
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