重介悬浮液密度自动控制系统的设计与开发
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摘要
重介选煤是按煤和矸石的密度不同进行分选的,但是由于精煤和矸石的密度都大于1,也就是说都大于水的密度,因此不能直接在水中分选。要想实现按密度分选,这就需要配置密度大于水的的液体,即重介悬浮液。重介悬浮液由密度不同的固相和液相组成,固相微粒分散于液相之中。在重介选煤中,重介悬浮液一般用磁铁矿粉配制,实际生产中,固相和液相包括磁铁矿粉、煤泥、水三部分。这样将原煤放入该密度的液体中,按阿基米德原理,大于液体密度的下沉,小于液体密度的上浮。
模糊控制(fuzzy control)是一种模仿现场操作人员的人工操作而发展起来的一种智能控制。面对一些过程控制中的时变性,现场随机干扰,惯性滞后性的对象,无法按照固定不变的策略进行控制,所以重新研究人工控制行为特点,运用模糊控制器替代人的大脑,模仿现场操作人员的操作经验而实现对复杂对象的控制。
在重介分选生产过程自动控制方面,为提高控制精度,目前国际国内均采用PID控制,采用了PID调节器参数整定与在线修改。分析系统特征,提出运用自校正原理设计控制系统方案,给出其控制算法。新建重介选煤厂基本都实现了悬浮液密度的自动化控制,部分老厂也在进行密度自动控制的改造,控制技术采用了成熟可靠的PID控制算法。
密度自动控制系统由两部分组成,其一：悬浮液密度高于给定密度时,通过控制管道上的补水阀开度的大小自动加水,将密度降低到设定的分选值；其二：悬浮液密度较低及煤泥含量较高时,则需要控制分流阀动作。具体工作过程是：当测量密度高于给定密度时,驱动电动执行器工作,进行补水,使密度逐步降低,这一过程是降低悬浮液密度的过程。当测量密度低于给定密度时,电动执行器执行机构控制分流阀开大,并将浓缩后的悬浮液返回合格悬浮液桶,使密度逐步回升,直至密度测量信号与外给定信号相等为止,此时电动执行器工作在一稳定的位置上,这一过程是提高悬浮液密度的过程。
然而当实现悬浮液密度自动调控时,在自动分流这一环节上,合介桶获得浓介需经过稀介桶、磁选机,而这一过程需要一定的时间,是典型的大惯性、大滞后过程控制,仅仅采用传统的PID控制不可避免的要出现超调和振荡现象。目前在选煤厂里,大多是在补水这一环节实现了真正的自动化,而在打分流这一环节上由于还在实行人工的控制,根据工作人员的经验进行实时的调节。仅靠人工控制导致悬浮液密度波动大,精煤灰分超标或精煤产率降低,岗位司机工作负荷大。
为了提高选煤的分选精度,急需将分流这一环节也实现自动化。如果这一环节也是实现自动化,其不仅减轻岗位司机工作负荷,还将会优化产品结构,提高产品质量,增加企业效益,向优质、高效、洁净生产方向发展。
基于课题对象,结合实际情况,它的补水装置安装在离斜轮分选机较近的管道上,它的动作能够较快影响到分选密度；而分流的装置的动作距离比较长远,过程缓慢滞后,需要较长的时间才能体现到分选密度的变化上。这样我们采用补水阀动作用PID参与控制,根据现场的使用经验证明这种方式是可行的。而分流这个过程由于其大惯性、大滞后和参数时变的不确定过程这样的特性,采用模糊控制就能很好的解决这个问题。
针对上述情况,在本课题中我们积极探索模糊控制在重介分选过程控制中的应用,建立了多变量输入输出的模糊控控制结构。采用PLC作为系统的模糊控制器,建立了重介质悬浮液的密度的补水PID控制与分流动作的模糊控制的复合模糊控制方案。
Dense medium coal separation is based on different densities of coal and gangue, but the density of coal and waste rock are greater than l,that is greater than the density of water, so separation can not be directly in the water.To achieve separation by density, it needs to configure the liquid that density is greater than water, that is dense medium suspension. Dense medium suspension is formed by the solid and liquid with different density, solid particles dispersing in liquid. In dense medium coal separation, dense medium suspension is prepared with magnetite powder, solid and liquid phases include magnetite powder, slurry and water in the actual production. Raw coal is put into the liquid with this density, some with the density less than liquid sink, others float by Archimedes.
Fuzzy control is an intelligent control developing by imitation of manual operation of field operators. The object with time-varying of process control, field random noise, inertial lag can not be controlled in accordance with the fixed strategy, so re-examine the characteristics of human control behavior, replace human brain by the fuzzy controller, imitate the operation experience of field operators to achieve control of complex objects.
In the automatic control of dense medium separation production process, in order to improve control accuracy, PID control are used in international and domestic at present, using PID controller parameter tuning and line modification, establishing mathematical model of dense medium separation process control system according to the dynamic relationship of the process parameters. Analysis system characteristics, propose to design control system by the use of self-tuning principle, and give the control algorithm. Basically the new HM coal preparation plants achieve the automatic control of dense medium suspension, some of the old plants are also under the transformation of density automatic control, and the control technology uses a mature and reliable PID control algorithm.
Density control system consists of two parts, first:when suspension density is higher than the given density, automatic water by controlling the opening size of pipe supply water valve to reduce the density of separation to the set value; Second:when suspension density is lower and slime content is high, need to control the shunt valve action. Specific work process is:when measured density is higher than a given density, drive electric actuators to supply water, gradually reducing the density, this process is to reduce the suspension density. When measured the density is lower than a given density, the electric actuator control the shunt valve to open a large, and return concentrated suspension to the qualified suspension barrel, so that the density gradually increased until the density measurement signal equal to the external given signal, at this point the electric actuators work in a stable position, the process is to improve the suspension density.
However, when achieve automatic control to the suspension density, in the automatic diversion, qualified media barrels need to obtain over-dense medium through dilute medium barrel and magnetic separator, and this process takes some time, is a typical large inertia, large time delay process control, overshoot and oscillations are inevitable just using the traditional PID control. At present in coal separation plant, in this part of replenishment is mostly for true automation; in this part of the shunt is still the implementation of the manual control in real time adjustment according to the experience of staff. Manual control alone led to suspension density fluctuations in large, clean coal ash exceeded or the yield decreased the workload driver's big job. To improve the accuracy of coal preparation, this part of the shunt also an urgent need to be automated. If this part is automated, which not only reduce the workload of the driver position, it also will optimize the product structure, improve product quality, increase enterprise efficiency, to high-quality, efficient and clean production.
Based on subject object and the actual situation, replenishment is installed on the pipe nearly to inclined lifting wheel separator, it moves quickly and enables to affect the separation density; The diversion device moves away from longer-term, slow and lag process, take a long time to reflect in the separation density changes. So PID involved in controlling replenishment valve, this approach proved to be feasible according to the field experience. The shunt process has large inertia and large delay and parameter uncertain time-varying characteristics, the fuzzy control can be a good solution to this problem. For the above, this issue explores the application of fuzzy control in the dense medium separation process control; establishes a fuzzy control structure with multi-variable input and output. Using PLC as the system fuzzy controller proposes fuzzy control scheme that composite replenishment PID control and shunt fuzzy control of the dense medium suspension density.
模糊控制(fuzzy control)是一种模仿现场操作人员的人工操作而发展起来的一种智能控制。面对一些过程控制中的时变性,现场随机干扰,惯性滞后性的对象,无法按照固定不变的策略进行控制,所以重新研究人工控制行为特点,运用模糊控制器替代人的大脑,模仿现场操作人员的操作经验而实现对复杂对象的控制。
在重介分选生产过程自动控制方面,为提高控制精度,目前国际国内均采用PID控制,采用了PID调节器参数整定与在线修改。分析系统特征,提出运用自校正原理设计控制系统方案,给出其控制算法。新建重介选煤厂基本都实现了悬浮液密度的自动化控制,部分老厂也在进行密度自动控制的改造,控制技术采用了成熟可靠的PID控制算法。
密度自动控制系统由两部分组成,其一：悬浮液密度高于给定密度时,通过控制管道上的补水阀开度的大小自动加水,将密度降低到设定的分选值；其二：悬浮液密度较低及煤泥含量较高时,则需要控制分流阀动作。具体工作过程是：当测量密度高于给定密度时,驱动电动执行器工作,进行补水,使密度逐步降低,这一过程是降低悬浮液密度的过程。当测量密度低于给定密度时,电动执行器执行机构控制分流阀开大,并将浓缩后的悬浮液返回合格悬浮液桶,使密度逐步回升,直至密度测量信号与外给定信号相等为止,此时电动执行器工作在一稳定的位置上,这一过程是提高悬浮液密度的过程。
然而当实现悬浮液密度自动调控时,在自动分流这一环节上,合介桶获得浓介需经过稀介桶、磁选机,而这一过程需要一定的时间,是典型的大惯性、大滞后过程控制,仅仅采用传统的PID控制不可避免的要出现超调和振荡现象。目前在选煤厂里,大多是在补水这一环节实现了真正的自动化,而在打分流这一环节上由于还在实行人工的控制,根据工作人员的经验进行实时的调节。仅靠人工控制导致悬浮液密度波动大,精煤灰分超标或精煤产率降低,岗位司机工作负荷大。
为了提高选煤的分选精度,急需将分流这一环节也实现自动化。如果这一环节也是实现自动化,其不仅减轻岗位司机工作负荷,还将会优化产品结构,提高产品质量,增加企业效益,向优质、高效、洁净生产方向发展。
基于课题对象,结合实际情况,它的补水装置安装在离斜轮分选机较近的管道上,它的动作能够较快影响到分选密度；而分流的装置的动作距离比较长远,过程缓慢滞后,需要较长的时间才能体现到分选密度的变化上。这样我们采用补水阀动作用PID参与控制,根据现场的使用经验证明这种方式是可行的。而分流这个过程由于其大惯性、大滞后和参数时变的不确定过程这样的特性,采用模糊控制就能很好的解决这个问题。
针对上述情况,在本课题中我们积极探索模糊控制在重介分选过程控制中的应用,建立了多变量输入输出的模糊控控制结构。采用PLC作为系统的模糊控制器,建立了重介质悬浮液的密度的补水PID控制与分流动作的模糊控制的复合模糊控制方案。
Dense medium coal separation is based on different densities of coal and gangue, but the density of coal and waste rock are greater than l,that is greater than the density of water, so separation can not be directly in the water.To achieve separation by density, it needs to configure the liquid that density is greater than water, that is dense medium suspension. Dense medium suspension is formed by the solid and liquid with different density, solid particles dispersing in liquid. In dense medium coal separation, dense medium suspension is prepared with magnetite powder, solid and liquid phases include magnetite powder, slurry and water in the actual production. Raw coal is put into the liquid with this density, some with the density less than liquid sink, others float by Archimedes.
Fuzzy control is an intelligent control developing by imitation of manual operation of field operators. The object with time-varying of process control, field random noise, inertial lag can not be controlled in accordance with the fixed strategy, so re-examine the characteristics of human control behavior, replace human brain by the fuzzy controller, imitate the operation experience of field operators to achieve control of complex objects.
In the automatic control of dense medium separation production process, in order to improve control accuracy, PID control are used in international and domestic at present, using PID controller parameter tuning and line modification, establishing mathematical model of dense medium separation process control system according to the dynamic relationship of the process parameters. Analysis system characteristics, propose to design control system by the use of self-tuning principle, and give the control algorithm. Basically the new HM coal preparation plants achieve the automatic control of dense medium suspension, some of the old plants are also under the transformation of density automatic control, and the control technology uses a mature and reliable PID control algorithm.
Density control system consists of two parts, first:when suspension density is higher than the given density, automatic water by controlling the opening size of pipe supply water valve to reduce the density of separation to the set value; Second:when suspension density is lower and slime content is high, need to control the shunt valve action. Specific work process is:when measured density is higher than a given density, drive electric actuators to supply water, gradually reducing the density, this process is to reduce the suspension density. When measured the density is lower than a given density, the electric actuator control the shunt valve to open a large, and return concentrated suspension to the qualified suspension barrel, so that the density gradually increased until the density measurement signal equal to the external given signal, at this point the electric actuators work in a stable position, the process is to improve the suspension density.
However, when achieve automatic control to the suspension density, in the automatic diversion, qualified media barrels need to obtain over-dense medium through dilute medium barrel and magnetic separator, and this process takes some time, is a typical large inertia, large time delay process control, overshoot and oscillations are inevitable just using the traditional PID control. At present in coal separation plant, in this part of replenishment is mostly for true automation; in this part of the shunt is still the implementation of the manual control in real time adjustment according to the experience of staff. Manual control alone led to suspension density fluctuations in large, clean coal ash exceeded or the yield decreased the workload driver's big job. To improve the accuracy of coal preparation, this part of the shunt also an urgent need to be automated. If this part is automated, which not only reduce the workload of the driver position, it also will optimize the product structure, improve product quality, increase enterprise efficiency, to high-quality, efficient and clean production.
Based on subject object and the actual situation, replenishment is installed on the pipe nearly to inclined lifting wheel separator, it moves quickly and enables to affect the separation density; The diversion device moves away from longer-term, slow and lag process, take a long time to reflect in the separation density changes. So PID involved in controlling replenishment valve, this approach proved to be feasible according to the field experience. The shunt process has large inertia and large delay and parameter uncertain time-varying characteristics, the fuzzy control can be a good solution to this problem. For the above, this issue explores the application of fuzzy control in the dense medium separation process control; establishes a fuzzy control structure with multi-variable input and output. Using PLC as the system fuzzy controller proposes fuzzy control scheme that composite replenishment PID control and shunt fuzzy control of the dense medium suspension density.
引文
[1]刘峰,叶大武.我国选煤工业主要技术装备现状与今后发展的建议[J].选美技术,2004(5)：1-3.
[2]谢广元.选矿学[M].徐州：中国矿业大学出版社,2001：495-514.
[3]祁泽民,符东旭.选煤用重介质悬浮液性质分析[J].重介质选煤技术会议论文集,2008,36(6)：34-40.
[4]赵春祥,叶桂森.重介质选煤过程控制模型及控制算法的研究[J].煤炭学报,2000,25：196-199.
[5]李梁才,袁文春,刘晓东.“十五”双供介重介选煤新工艺密度自动控制系统设计[J].选煤技术,2009,(4)：75-77.
[6]李正平等.γ射线密度计系统的硬软件设计[J].核电子学与探测技术,2003,23(6)：560-563.
[7]卢晓.浅谈重介选煤厂介质密度自动控制系统[J].煤质技术,2002,3：13-14.
[8]李存蔚,荣焕成,孙林兔.重介密度自动控制系统研究[J].选煤技术,2002,4：45-48.
[9]张竹英.重介悬浮液密度计液位的检测与自动控制[J].山西焦煤科技,2009,10：37-40.
[10]贾为利,匡亚莉,王光辉等.选煤企业自动控制系统的应用及发展[J].煤炭工程,2009,第五期：121-123.
[11]陈章宝.基于PLC的重介选煤工艺模糊控制的研究[D]安徽：安徽理工大学,2006.
[12]张宇等.基于S7-300PLC的电加热器模糊控制编程实现[J].南昌大学学报,2005,27(3)：59-63.
[13]王靖飞.动物疾病诊断专家系统的研究与应用[D].哈尔滨：东北农业大学,2002.
[14]汪小澄,方强.基于PLC的模糊控制研究[J].武汉大学学报,2002,35(3)：79-81.
[15]武晓明.基于模糊控制方法的子宫内膜热疗仪温度控制系统[D].山东：山东科 技大学,2004.
[16]张建民,王涛,王忠礼.智能控制原理及其应用[M].北京：冶金工业出版社,2003.
[17]张宇等.基于重介悬浮液密度自动控制系统的分析[J].阜阳师范学院学报,1996,4：77-80.
[18]王瑞红.重介悬浮液密度自动控制系统的应用[J].煤炭技术,1999,18(3)：23-27.
[19]郭秀清等.基于重介悬浮液密度及液位的检测与自动控制[J].煤炭技术,1999,(6)：40-42.
[20]陈章宝.基于PLC的重介选煤工艺模糊控制的研究[D].安徽：安徽理工大学,2006.
[21]徐立.控制工程基础[M].杭州：浙江大学出版社,2007,4-177.
[22]李士勇.模糊控制神经控制和智能控制论[M].哈尔滨：哈尔滨工业大学出版社,1998,174-252.
[23]瞿枫,徐忠宏,孙冀.基于西门子S7-300PLC的模糊控制实现[J].南京师范大学学报,2007,7(4)：23-27.
[24]郝俊青.洗选厂洗煤车间PLC控制及其组态[D].太原：太原理工大学,2007.
[25]周力,崔祚.模糊控制用PLC实现的方法探讨[J].自动化与仪器仪表,2006,(5)：29-30.
[26]李平.模糊控制在S7-300PLC中的实现[J].工程技术,2010,(2)：281-283.
[27]廖常初.S7-300/400PLC应用技术[M].北京：机械工业出版社,2005.
[28]西门子(中国)有限公司自动化与驱动集团.西门子S7-300PLC[M].北京：北京航空航天大学出版社,2004.
[29]甄立东.西门子WinCC V7基础与应用[M].北京：机械工业出版社,2011.
[30]胡健.西门子S7-300可编程控制器应用教程[M].北京：机械工业出版社,2008.
[31]陈志新,宗学军.电器与PLC控制技术[M].北京：中国林业出版社,北京大学出版社,2005.
[32]方泳龙,邹乃威,杨志华等.汽车制动专家系统入机界面设计和知识库的建立[J].农业机械学报,2006,37(6)：23-26.
[33]刘晓霞等.时滞系统的自适应模糊控制器的研究[J].信息与控制,2003,32(3)：285-288.
[34]李丽军,余军.量化因子和比例因子对模糊控制器的影响及修正[J].韶关大学学报.1999,20(2)：9-12
[35]李祖欣. MATLAB在模糊控制系统设计和仿真的应用[J].系统仿真学报,200315(1)131-134.
[36]宋瑞,林青家,夏佃秀.用MATLAB的SIMULINK进行模糊控制系统仿真,山东冶金,2003,第4期：75-80.
[37]石辛民,郝整清.模糊控制及其MARLAB仿真[M].北京：清华大学出版社,北京交通大学出版社,2008.
[38]Serenger.LAOCOADEMS medium processing technology[J]. Aufbereitungs-Technik,1998,9:467-48
[39]D Baillie.Three product Larcodems'separator demostration,installat-ion and performance testing[R].Final report EUR-17155-EN,1997:138-142
[40]S.N.Vasil, ev, D.V.Volosnikov, A Programmable device for Experiments Employing a Superheated Probe in the Pulsed Operation Mode, Instruments and Experimental Techniques,2004,47(4):539-544
[41]HiroshiSakai, TatsuoMasuda, High—speed CDP for FP2SH programmable Controller, A&I Technical Report.2000, (70):64-68
[42]SIEMENS, SIRATIC SS — 135U Progratamable Control let Manual
[43]Lyu M R, Society Handbook of Software Retiability Engineering, IEEE ComputerPress, 1996
[44]OhamanMartin, Johnasson, Stenaf, Arzen, Karl-Erik.Implementation aspects of The PLC standard IEC1131-3[J].Conrtol Engineering Practice,1998,6(8):547-555
[45]Ho W K Hang C C, Cao L S. Tuning of PID controllers based on gaill and phase margin specification[J]. Automatia.1995,31:497-502
[46]Goberhansingh E, Cluett W R. Evaluation of an industrial PID Auto-tamer[J]. Lecture Notes Control and Information Science.1998,137: 295-305
[47]Astrom ICJ., Hang C C. Persson P and Ho W K. Towards Intelligent PID Control [J]. Automation.2002,28(1):1-9
[48]M Zhuang, D. P. Athermn. Automatic tuning of optimum PID controllers[J]. IEE Proceedings Control and Applications.1998,140:216-224
[2]谢广元.选矿学[M].徐州：中国矿业大学出版社,2001：495-514.
[3]祁泽民,符东旭.选煤用重介质悬浮液性质分析[J].重介质选煤技术会议论文集,2008,36(6)：34-40.
[4]赵春祥,叶桂森.重介质选煤过程控制模型及控制算法的研究[J].煤炭学报,2000,25：196-199.
[5]李梁才,袁文春,刘晓东.“十五”双供介重介选煤新工艺密度自动控制系统设计[J].选煤技术,2009,(4)：75-77.
[6]李正平等.γ射线密度计系统的硬软件设计[J].核电子学与探测技术,2003,23(6)：560-563.
[7]卢晓.浅谈重介选煤厂介质密度自动控制系统[J].煤质技术,2002,3：13-14.
[8]李存蔚,荣焕成,孙林兔.重介密度自动控制系统研究[J].选煤技术,2002,4：45-48.
[9]张竹英.重介悬浮液密度计液位的检测与自动控制[J].山西焦煤科技,2009,10：37-40.
[10]贾为利,匡亚莉,王光辉等.选煤企业自动控制系统的应用及发展[J].煤炭工程,2009,第五期：121-123.
[11]陈章宝.基于PLC的重介选煤工艺模糊控制的研究[D]安徽：安徽理工大学,2006.
[12]张宇等.基于S7-300PLC的电加热器模糊控制编程实现[J].南昌大学学报,2005,27(3)：59-63.
[13]王靖飞.动物疾病诊断专家系统的研究与应用[D].哈尔滨：东北农业大学,2002.
[14]汪小澄,方强.基于PLC的模糊控制研究[J].武汉大学学报,2002,35(3)：79-81.
[15]武晓明.基于模糊控制方法的子宫内膜热疗仪温度控制系统[D].山东：山东科 技大学,2004.
[16]张建民,王涛,王忠礼.智能控制原理及其应用[M].北京：冶金工业出版社,2003.
[17]张宇等.基于重介悬浮液密度自动控制系统的分析[J].阜阳师范学院学报,1996,4：77-80.
[18]王瑞红.重介悬浮液密度自动控制系统的应用[J].煤炭技术,1999,18(3)：23-27.
[19]郭秀清等.基于重介悬浮液密度及液位的检测与自动控制[J].煤炭技术,1999,(6)：40-42.
[20]陈章宝.基于PLC的重介选煤工艺模糊控制的研究[D].安徽：安徽理工大学,2006.
[21]徐立.控制工程基础[M].杭州：浙江大学出版社,2007,4-177.
[22]李士勇.模糊控制神经控制和智能控制论[M].哈尔滨：哈尔滨工业大学出版社,1998,174-252.
[23]瞿枫,徐忠宏,孙冀.基于西门子S7-300PLC的模糊控制实现[J].南京师范大学学报,2007,7(4)：23-27.
[24]郝俊青.洗选厂洗煤车间PLC控制及其组态[D].太原：太原理工大学,2007.
[25]周力,崔祚.模糊控制用PLC实现的方法探讨[J].自动化与仪器仪表,2006,(5)：29-30.
[26]李平.模糊控制在S7-300PLC中的实现[J].工程技术,2010,(2)：281-283.
[27]廖常初.S7-300/400PLC应用技术[M].北京：机械工业出版社,2005.
[28]西门子(中国)有限公司自动化与驱动集团.西门子S7-300PLC[M].北京：北京航空航天大学出版社,2004.
[29]甄立东.西门子WinCC V7基础与应用[M].北京：机械工业出版社,2011.
[30]胡健.西门子S7-300可编程控制器应用教程[M].北京：机械工业出版社,2008.
[31]陈志新,宗学军.电器与PLC控制技术[M].北京：中国林业出版社,北京大学出版社,2005.
[32]方泳龙,邹乃威,杨志华等.汽车制动专家系统入机界面设计和知识库的建立[J].农业机械学报,2006,37(6)：23-26.
[33]刘晓霞等.时滞系统的自适应模糊控制器的研究[J].信息与控制,2003,32(3)：285-288.
[34]李丽军,余军.量化因子和比例因子对模糊控制器的影响及修正[J].韶关大学学报.1999,20(2)：9-12
[35]李祖欣. MATLAB在模糊控制系统设计和仿真的应用[J].系统仿真学报,200315(1)131-134.
[36]宋瑞,林青家,夏佃秀.用MATLAB的SIMULINK进行模糊控制系统仿真,山东冶金,2003,第4期：75-80.
[37]石辛民,郝整清.模糊控制及其MARLAB仿真[M].北京：清华大学出版社,北京交通大学出版社,2008.
[38]Serenger.LAOCOADEMS medium processing technology[J]. Aufbereitungs-Technik,1998,9:467-48
[39]D Baillie.Three product Larcodems'separator demostration,installat-ion and performance testing[R].Final report EUR-17155-EN,1997:138-142
[40]S.N.Vasil, ev, D.V.Volosnikov, A Programmable device for Experiments Employing a Superheated Probe in the Pulsed Operation Mode, Instruments and Experimental Techniques,2004,47(4):539-544
[41]HiroshiSakai, TatsuoMasuda, High—speed CDP for FP2SH programmable Controller, A&I Technical Report.2000, (70):64-68
[42]SIEMENS, SIRATIC SS — 135U Progratamable Control let Manual
[43]Lyu M R, Society Handbook of Software Retiability Engineering, IEEE ComputerPress, 1996
[44]OhamanMartin, Johnasson, Stenaf, Arzen, Karl-Erik.Implementation aspects of The PLC standard IEC1131-3[J].Conrtol Engineering Practice,1998,6(8):547-555
[45]Ho W K Hang C C, Cao L S. Tuning of PID controllers based on gaill and phase margin specification[J]. Automatia.1995,31:497-502
[46]Goberhansingh E, Cluett W R. Evaluation of an industrial PID Auto-tamer[J]. Lecture Notes Control and Information Science.1998,137: 295-305
[47]Astrom ICJ., Hang C C. Persson P and Ho W K. Towards Intelligent PID Control [J]. Automation.2002,28(1):1-9
[48]M Zhuang, D. P. Athermn. Automatic tuning of optimum PID controllers[J]. IEE Proceedings Control and Applications.1998,140:216-224
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