基于嵌入式的温度控制系统与算法研究
摘要
表面粘贴技术是一门涉及元器件、组装设备、焊接方法和组装辅助材料等内容,将电子元器件组装或贴装到印刷电路板(PCB)上的综合技术,被认为是电子组装技术的一次革命。随着国际信息产业无铅化的发展和IC芯片的技术革新,对电子信息产品无铅化需要的技术——回流焊接工艺提出了新的要求:利用更先进的控制方式在高温度、高温差、温度均匀、温度柔性化和垂直烘烤下进行无铅焊料的焊接,以达到提高生产质量,节约能量的目的。
本文设计了基于嵌入式的温度控制系统,首先介绍温度控制的硬件结构,对主要电路进行设计,采用PHILIPS公司的LPC2212做为温度控制系统的核心处理器,在回流焊上植入嵌入式实时操作系统μC/OS-Ⅱ,搭建了一个任务管理平台,通过实时内核来对任务进行调度、管理,完成对回流焊工作任务的控制,采用μC/OS-Ⅱ为基础操作平台的设计工业控制系统,可以克服传统的采用前后台控制和中断响应方式所难以很好解决的实时响应差、控制效率低的缺点。实际运行结果表明该系统稳定性好,可靠性高,人机界面友好,维护简单。
参数优化是许多科学、工程问题以及社会经济活动中的重要研究内容。针对该系统的实际情况,提出了基于进化算法的PID整定策略,主要讲了遗传算法和微粒子群算法,其中遗传算法能通过自学习能力对模型的控制参数进行了优化,找到了较好的控制参数,本文借助积分分离算法在阶跃响应的仿真中的对比,实验表明遗传算法的PID整定策略要大大优于传统PID算法。最后通过采用PSO算法对PID参数进行了优化,仿真结果表明该算法响应时间短,稳定收敛,精确度高,易于并行化,是一种效率很高的寻优方法,是PID参数优化的理想方法。
Surface mounting technology (SMT) is used to mount the electronic components onthe PCB. It treat of the components、mounting equipment、soldering measure andmaterials, and it also has been considered as a revolution in electronic mounting fields. With lead-free development of international IT industry and IC chip technical improvement, the new request to electronic information products lead-free technology that is availability in reflow jointing have brought forward: jointing lead-free solders Making use of more advanced control method under the condition of high temperature, high temperature difference, temperature equation, temperature flexibility and perpendicularity bakes, to realize the goal of enhancing the products' quality and saving the energy.
This paper designed the temperature control system based on embedded , first introduced the hardware structure of the temperature control , and designed the main circuit, adopt the LPC2212 as the core processor of the temperature control system, running speed and handling complex data have many SCM unmatched performance, in reflow transplant the embedded real-time operating systemμC/OS-II, set up a task management platform, through real-time kernel to schedule and manage the tasks , to complete the control of the reflow soldering tasks, the design of industrial control systems useμC/OS- II as operating platform, can be overcome traditional Taiwan before and after the introduction of control and difficult to interrupt response by the good way to resolve the real-time response poor, low-efficiency control weaknesses. Actual operating results show that the system has good stability, high reliability, friendly Man-machine Interface, easy maintenance.
The problem of parameters optimization is involved in many scientific, engineering and economic fields. founding on this temperature control system,evolutionary algorithm is proposed based on the PID tuning strategy, focused on genetic algorithms and particles swarm algorithm, the genetic algorithm PID turning strategy have been brought forward. It can optimize the system model structure through the self-learning ability, and turn up the optimized parameter of the model. The paper utilize the step response simulate curves of the Integral-Separated PID algorithm to comparing to the effect, finally, PSO is used to optimize the PID parameters, The simulation results show that the algorithm short response time, stability, convergence, high accuracy, easy to concurrentoperation. It is an ideal method for optimizing PID parameters.
本文设计了基于嵌入式的温度控制系统,首先介绍温度控制的硬件结构,对主要电路进行设计,采用PHILIPS公司的LPC2212做为温度控制系统的核心处理器,在回流焊上植入嵌入式实时操作系统μC/OS-Ⅱ,搭建了一个任务管理平台,通过实时内核来对任务进行调度、管理,完成对回流焊工作任务的控制,采用μC/OS-Ⅱ为基础操作平台的设计工业控制系统,可以克服传统的采用前后台控制和中断响应方式所难以很好解决的实时响应差、控制效率低的缺点。实际运行结果表明该系统稳定性好,可靠性高,人机界面友好,维护简单。
参数优化是许多科学、工程问题以及社会经济活动中的重要研究内容。针对该系统的实际情况,提出了基于进化算法的PID整定策略,主要讲了遗传算法和微粒子群算法,其中遗传算法能通过自学习能力对模型的控制参数进行了优化,找到了较好的控制参数,本文借助积分分离算法在阶跃响应的仿真中的对比,实验表明遗传算法的PID整定策略要大大优于传统PID算法。最后通过采用PSO算法对PID参数进行了优化,仿真结果表明该算法响应时间短,稳定收敛,精确度高,易于并行化,是一种效率很高的寻优方法,是PID参数优化的理想方法。
Surface mounting technology (SMT) is used to mount the electronic components onthe PCB. It treat of the components、mounting equipment、soldering measure andmaterials, and it also has been considered as a revolution in electronic mounting fields. With lead-free development of international IT industry and IC chip technical improvement, the new request to electronic information products lead-free technology that is availability in reflow jointing have brought forward: jointing lead-free solders Making use of more advanced control method under the condition of high temperature, high temperature difference, temperature equation, temperature flexibility and perpendicularity bakes, to realize the goal of enhancing the products' quality and saving the energy.
This paper designed the temperature control system based on embedded , first introduced the hardware structure of the temperature control , and designed the main circuit, adopt the LPC2212 as the core processor of the temperature control system, running speed and handling complex data have many SCM unmatched performance, in reflow transplant the embedded real-time operating systemμC/OS-II, set up a task management platform, through real-time kernel to schedule and manage the tasks , to complete the control of the reflow soldering tasks, the design of industrial control systems useμC/OS- II as operating platform, can be overcome traditional Taiwan before and after the introduction of control and difficult to interrupt response by the good way to resolve the real-time response poor, low-efficiency control weaknesses. Actual operating results show that the system has good stability, high reliability, friendly Man-machine Interface, easy maintenance.
The problem of parameters optimization is involved in many scientific, engineering and economic fields. founding on this temperature control system,evolutionary algorithm is proposed based on the PID tuning strategy, focused on genetic algorithms and particles swarm algorithm, the genetic algorithm PID turning strategy have been brought forward. It can optimize the system model structure through the self-learning ability, and turn up the optimized parameter of the model. The paper utilize the step response simulate curves of the Integral-Separated PID algorithm to comparing to the effect, finally, PSO is used to optimize the PID parameters, The simulation results show that the algorithm short response time, stability, convergence, high accuracy, easy to concurrentoperation. It is an ideal method for optimizing PID parameters.
引文
[1]Reinhard Edison Powell.Development of Convective solder reflow and Projection moire System and model for PWBA Warpage Prediction:[Paper of doctor degree].America.George W.Woodruff School
[2]张文典.21世纪SMT发展趋势及对策.电子工艺技术,2001,(1):1-3
[3]胡志勇.贴片设备发展的新趋势.世界电子元器件,2001,(10):39-40
[4]史建卫,何鹏等.再流焊技术的新发展.电子工业专用设备,2005,(1):63-67
[5]Nele Van Steenberge,Bart Vandevelde,Inge Schildermans etc.Analytical and Finite Element Models of the Thermal Behavior for Lead-free Soldering Processes in Electronic Assembly.Thermal,Mechanical and Muti-Physics Simulation and Experiments in Micro-Electronics and Micro-Systems,2005.EuroSimE 2005.Proceedings of the 6~(th)International Conference on.April 2005.675-680
[6]彭传谦.红外回流焊环境温度的设置及影响焊接质量的几个因素.船舰电子工程,2001,(2):62-65
[7]李敏.热风回流焊机温度控制软计算建模与系统设计:[硕士学位论文].湖南长沙,中南大学.2005
[8]郝应征,王彩云.再流焊接的一般要求及温度测试方法.电子工艺技术,1999,20(4):151-153
[9]俊伟,聂延平,赵志平.再流区工艺参数对焊接可靠性的影响.电子工艺技术.2001,22(2):62-63
[10]王强.基于ARM控制器的渗炭炉温度控制系统的设计与实现.电子技术应用,2006,(6):85-87
[11]Jean.Labrosse.嵌入式实时操作系统μC/OS-Ⅱ(第2版).邵贝贝等译。北京:北京航天航,2003
[12]田泽.嵌入式系统开发与应用.北京:北京航空航天大学出版社,2004:5-62
[13]周立功等编著,ARM与嵌入式系统基础教程,广州周立功单片机发展有限公司,2004,11
[14]Carsten Nitsch,Karlheinz Weiss,etc.Embedded System Architecture DesignBsaed on Real-Time Emulation,2003,2
[15]Richard C.Dorf Rovert H.Bishop.Modern control systems[M].USA:Addison Wesley Longman,Inc,1998
[16]汪学军.多温区自动测控系统控制模型的建立与研究:[硕士学位论文],长沙,中南大学,2007
[17]刘金琨.先进PID控制及其MATLAB仿真,北京:电子工业出版社,2003:130-150
[18]王伟,张晶涛,柴天佑.PID参数先进整定方法综述,自动化学报.2000,26(3):347-355
[19]曾自力.基于进化算法的PID控制系统设计方法研究:[硕士学位论文].江苏南京,南京理工大学,2006
[20]蒋新华.自适应PID控制.信息与控制.1988,17(5):41-50
[21]Koivo H N,Tanttu J T.Tuning of PID controllers:survey of SISO and MIMO techniques.In:Preprints of IFAC International Symp.on Intelligent Tuning and Adaptive Control,Session 1,Singapore,1991.
[22]Astrom K J,Hagglund T,Hang C C et al.Automatic tuning and adaptation for PIDcontrollers——A survey.Control Eng.Practice,1993,1(4):699-714.
[23]Astrom K J,Hagglund T.Automatic Tuning of PID Controllers.Research Triangle Park,North Carolina:Instrument Society of America,1988.
[24]Ziegler J G,Nichols N B.Optimum settings for automatic controllers.Trans.ASME,1942,64:759-768.
[25]王正志,薄涛,进化计算,国防科技大学出版社。
[26]Potter M.A.,de Jong K.A.A cooperative co-evolutionary approach to function optimization.In the third Parallel Problem Soving From Nature.Berlin,Germany,Sprinter-Verlag,1994,249-257
[27]王凌.智能优化算法及其应用.清华大学出版社,施普林格出版社,北京,2001
[28]Wei-Der Chang,Monlinera System Identification and Control Using a Real-Coded Genetic Algorithm.Journal of Applied Mathematical Modeling,2007(31):541-550
[29]Wei-Der Chang,A Multi-crossover Genetic Approach to Multivariable PID Controllers Tuning.Journal of Expert Systems with Applications,2007(33):620-626
[30]Jill Tao,Ning Wang,Xuejun Wang,Genetic Algorithm Based Recurrent Fuzzy Neural Network Modeling of Chemical Process.Pre-proceedings of the International Conference Bio-Inspired Computing-Theory and Applications, 2000:157-168
[31]李凯南,潘笑.自适应遗传算法在PID控制参数优化中的应用.邵阳学院学报.2006,(3):35-38
[32]邹凌,杨力,邹莹梅,基于遗传算法的PID参数寻优.江苏工业学院学报.2005,(3):41-44
[33]胡志宇.遗传算法在PID控制参数调节中的应用.重庆工业高等专科学校学报,2001,(3):24-26
[34]任占魁.基于遗传算法寻优的PID控制技术及应用.计算技术与自动化,2005,(2):36-38
[35]Yong P.Wang,Neville R.Watson,Hyeng H.Chong.Modified genetic algorithm approach to design of an optimal PID control for AC-DC transmission systems.Journal of Electrical Power and Energy Systems,2002(24):59-69
[36]Kennedy J.,Eberhart R.C.Particle swarm optimization.Proceedings of the IEEE International Conference on Neural Networks,1995,1942-1948
[37]Eberhart R.C.,Kennedy J.A new optimizer using particle swarm theory.Proceedings of the 6th International Symposium on Micro Machine and HumanScience,Nagoya,Japan,1995,39-43
[38]Millonas M.M.Swarm Phase Transition and Collective Intelligence.MA:Addison Wesley,1994
[39]向涛.基于热平衡机理的多温区动态建模及控制研究:[硕士学位论文].长沙,中南大学,2006
[40]周筠清编.传热学[M].北京:冶金工业出版社,1989:1-3
[41]PHILIPS公司.LPC2114/2124/2212/2214 USER MANUAL.PHILIPS公司2003.2
[42]Wayne Wolf.Principles of Embedded System Design,Computers AsComponents.2002
[43]Bushne111g.Networks and control.IEEE Control Systems Magazine,2001.Vol21,No.1
[44]Jae-Ho Lee.lmplementing priorit inheritance semaphore on uC/OS real-timekernel software Technologies for Future Embedded Systems,2003.IEEE Workshop on,May2003:15-16
[45]高超然、徐成等,32位嵌入式开发的发展与动向分析,2004:1-2
[46]陈鑫,嵌入式软件技术的现状与发展动向,软件世界,2001:2
[47]何小平,选择适合ARM的嵌入式操作系统,BMRfechInc,2003:5
[48]周立功等编著,ARM与嵌入式系统实验教程(一).北京:北京航天航空大学出版社,2004:5-6
[49]曹茂永,王霞.仪用放大器AD620及其应用.电测与仪表,2000,(10):49-52.
[50]李彦明,刘阳.采用精密线性光耦TIL300实现模拟量的隔离.国外电子元器件,2000,(2):29-30
[51]赵宁,陈明.嵌入式操作系统uC/OS-Ⅱ在ARM上的移植与应用.计算机应用与技术.2004 24(4):29-34
[52]李兴.虚拟仪器的软件开发.原子能科学技术.1999,33(2):125
[53]黄天戍,李诗晗,黄绵华.LabWindows/CVI中串行通信的实现.仪表术.2004,(4):11
[54]洪雪梅,郑立新,周凯汀.基于LabWindows/CVI的数字PID工程整定。福建电脑.2004.(9):67
[55]郑立新,周凯汀,龚勇,王永初.LabWindows/CVI与Matlab软接口技术及应用.自动化仪表.2004,(4):14.
[56]W.W.Tan,F.Lu,A.P.Loh,K.C.Tan,Modeling and Control of a Pilot PH Plant Using Genetic Algorithm.Journal of Engineering Applications of Artificial Intelligence,2005(18):485-494
[57]W.Huang,H.N.Lam,Using Genetic Algorithm to Optimize Controller Parameters for HVAC Systems.Journal of Energy and Buildings,1997(3):277-282.
[58]Reynolds ComputerC.Flocks,Graphics.Herds,and Schools:A Distributed Behavioral Model.1987.21(4):25-34
[59]Wilson,E.0.Sociobiology:The new synthesis,Cambridge,MA:Belknap Press,1975:321-329
[60]徐志成.基于微粒群优化的控制系统设计研究:[硕士学位论文].浙江杭州,浙江大学,2006
[61]侯志荣,吕振肃.基于MATLAB的粒子群优化算法及其应用.计算机仿真,2003,20(10):68-70
[2]张文典.21世纪SMT发展趋势及对策.电子工艺技术,2001,(1):1-3
[3]胡志勇.贴片设备发展的新趋势.世界电子元器件,2001,(10):39-40
[4]史建卫,何鹏等.再流焊技术的新发展.电子工业专用设备,2005,(1):63-67
[5]Nele Van Steenberge,Bart Vandevelde,Inge Schildermans etc.Analytical and Finite Element Models of the Thermal Behavior for Lead-free Soldering Processes in Electronic Assembly.Thermal,Mechanical and Muti-Physics Simulation and Experiments in Micro-Electronics and Micro-Systems,2005.EuroSimE 2005.Proceedings of the 6~(th)International Conference on.April 2005.675-680
[6]彭传谦.红外回流焊环境温度的设置及影响焊接质量的几个因素.船舰电子工程,2001,(2):62-65
[7]李敏.热风回流焊机温度控制软计算建模与系统设计:[硕士学位论文].湖南长沙,中南大学.2005
[8]郝应征,王彩云.再流焊接的一般要求及温度测试方法.电子工艺技术,1999,20(4):151-153
[9]俊伟,聂延平,赵志平.再流区工艺参数对焊接可靠性的影响.电子工艺技术.2001,22(2):62-63
[10]王强.基于ARM控制器的渗炭炉温度控制系统的设计与实现.电子技术应用,2006,(6):85-87
[11]Jean.Labrosse.嵌入式实时操作系统μC/OS-Ⅱ(第2版).邵贝贝等译。北京:北京航天航,2003
[12]田泽.嵌入式系统开发与应用.北京:北京航空航天大学出版社,2004:5-62
[13]周立功等编著,ARM与嵌入式系统基础教程,广州周立功单片机发展有限公司,2004,11
[14]Carsten Nitsch,Karlheinz Weiss,etc.Embedded System Architecture DesignBsaed on Real-Time Emulation,2003,2
[15]Richard C.Dorf Rovert H.Bishop.Modern control systems[M].USA:Addison Wesley Longman,Inc,1998
[16]汪学军.多温区自动测控系统控制模型的建立与研究:[硕士学位论文],长沙,中南大学,2007
[17]刘金琨.先进PID控制及其MATLAB仿真,北京:电子工业出版社,2003:130-150
[18]王伟,张晶涛,柴天佑.PID参数先进整定方法综述,自动化学报.2000,26(3):347-355
[19]曾自力.基于进化算法的PID控制系统设计方法研究:[硕士学位论文].江苏南京,南京理工大学,2006
[20]蒋新华.自适应PID控制.信息与控制.1988,17(5):41-50
[21]Koivo H N,Tanttu J T.Tuning of PID controllers:survey of SISO and MIMO techniques.In:Preprints of IFAC International Symp.on Intelligent Tuning and Adaptive Control,Session 1,Singapore,1991.
[22]Astrom K J,Hagglund T,Hang C C et al.Automatic tuning and adaptation for PIDcontrollers——A survey.Control Eng.Practice,1993,1(4):699-714.
[23]Astrom K J,Hagglund T.Automatic Tuning of PID Controllers.Research Triangle Park,North Carolina:Instrument Society of America,1988.
[24]Ziegler J G,Nichols N B.Optimum settings for automatic controllers.Trans.ASME,1942,64:759-768.
[25]王正志,薄涛,进化计算,国防科技大学出版社。
[26]Potter M.A.,de Jong K.A.A cooperative co-evolutionary approach to function optimization.In the third Parallel Problem Soving From Nature.Berlin,Germany,Sprinter-Verlag,1994,249-257
[27]王凌.智能优化算法及其应用.清华大学出版社,施普林格出版社,北京,2001
[28]Wei-Der Chang,Monlinera System Identification and Control Using a Real-Coded Genetic Algorithm.Journal of Applied Mathematical Modeling,2007(31):541-550
[29]Wei-Der Chang,A Multi-crossover Genetic Approach to Multivariable PID Controllers Tuning.Journal of Expert Systems with Applications,2007(33):620-626
[30]Jill Tao,Ning Wang,Xuejun Wang,Genetic Algorithm Based Recurrent Fuzzy Neural Network Modeling of Chemical Process.Pre-proceedings of the International Conference Bio-Inspired Computing-Theory and Applications, 2000:157-168
[31]李凯南,潘笑.自适应遗传算法在PID控制参数优化中的应用.邵阳学院学报.2006,(3):35-38
[32]邹凌,杨力,邹莹梅,基于遗传算法的PID参数寻优.江苏工业学院学报.2005,(3):41-44
[33]胡志宇.遗传算法在PID控制参数调节中的应用.重庆工业高等专科学校学报,2001,(3):24-26
[34]任占魁.基于遗传算法寻优的PID控制技术及应用.计算技术与自动化,2005,(2):36-38
[35]Yong P.Wang,Neville R.Watson,Hyeng H.Chong.Modified genetic algorithm approach to design of an optimal PID control for AC-DC transmission systems.Journal of Electrical Power and Energy Systems,2002(24):59-69
[36]Kennedy J.,Eberhart R.C.Particle swarm optimization.Proceedings of the IEEE International Conference on Neural Networks,1995,1942-1948
[37]Eberhart R.C.,Kennedy J.A new optimizer using particle swarm theory.Proceedings of the 6th International Symposium on Micro Machine and HumanScience,Nagoya,Japan,1995,39-43
[38]Millonas M.M.Swarm Phase Transition and Collective Intelligence.MA:Addison Wesley,1994
[39]向涛.基于热平衡机理的多温区动态建模及控制研究:[硕士学位论文].长沙,中南大学,2006
[40]周筠清编.传热学[M].北京:冶金工业出版社,1989:1-3
[41]PHILIPS公司.LPC2114/2124/2212/2214 USER MANUAL.PHILIPS公司2003.2
[42]Wayne Wolf.Principles of Embedded System Design,Computers AsComponents.2002
[43]Bushne111g.Networks and control.IEEE Control Systems Magazine,2001.Vol21,No.1
[44]Jae-Ho Lee.lmplementing priorit inheritance semaphore on uC/OS real-timekernel software Technologies for Future Embedded Systems,2003.IEEE Workshop on,May2003:15-16
[45]高超然、徐成等,32位嵌入式开发的发展与动向分析,2004:1-2
[46]陈鑫,嵌入式软件技术的现状与发展动向,软件世界,2001:2
[47]何小平,选择适合ARM的嵌入式操作系统,BMRfechInc,2003:5
[48]周立功等编著,ARM与嵌入式系统实验教程(一).北京:北京航天航空大学出版社,2004:5-6
[49]曹茂永,王霞.仪用放大器AD620及其应用.电测与仪表,2000,(10):49-52.
[50]李彦明,刘阳.采用精密线性光耦TIL300实现模拟量的隔离.国外电子元器件,2000,(2):29-30
[51]赵宁,陈明.嵌入式操作系统uC/OS-Ⅱ在ARM上的移植与应用.计算机应用与技术.2004 24(4):29-34
[52]李兴.虚拟仪器的软件开发.原子能科学技术.1999,33(2):125
[53]黄天戍,李诗晗,黄绵华.LabWindows/CVI中串行通信的实现.仪表术.2004,(4):11
[54]洪雪梅,郑立新,周凯汀.基于LabWindows/CVI的数字PID工程整定。福建电脑.2004.(9):67
[55]郑立新,周凯汀,龚勇,王永初.LabWindows/CVI与Matlab软接口技术及应用.自动化仪表.2004,(4):14.
[56]W.W.Tan,F.Lu,A.P.Loh,K.C.Tan,Modeling and Control of a Pilot PH Plant Using Genetic Algorithm.Journal of Engineering Applications of Artificial Intelligence,2005(18):485-494
[57]W.Huang,H.N.Lam,Using Genetic Algorithm to Optimize Controller Parameters for HVAC Systems.Journal of Energy and Buildings,1997(3):277-282.
[58]Reynolds ComputerC.Flocks,Graphics.Herds,and Schools:A Distributed Behavioral Model.1987.21(4):25-34
[59]Wilson,E.0.Sociobiology:The new synthesis,Cambridge,MA:Belknap Press,1975:321-329
[60]徐志成.基于微粒群优化的控制系统设计研究:[硕士学位论文].浙江杭州,浙江大学,2006
[61]侯志荣,吕振肃.基于MATLAB的粒子群优化算法及其应用.计算机仿真,2003,20(10):68-70