西门子PLC S7-300PID调试指南
PID调节温度控制实例（西门子S7-300）
PID调节温度控制实例（西门子S7-300）
控制要求
1.水罐水温设置在50℃
2.误差值在±1℃
硬件配置
设计方案
1.采样：使用 PT100 热电阻经过变送器把水缸温度传送给S7-300 PLC。
2. 数据的处理：在S7-300 PLC 中经过PID 调节运算输出模拟量信号到功率调节器中。
3.温度调节：在功率调节器中把对应的模拟量转化为对应的功率来驱动热得快；
程序编写
1.创建名称为PID调节的工程，添加CPU314C-2DP.西门子CPU314C-2DP，自带有模拟量输入输出通道，无需扩展模块，在这里我们要注意他们的地址，以及输入输出的测量类型与测量范围。
这次试验用的是4-20mA 的变送器，输出我们采用0-10V电压输出，这些参数需要在硬件组态时进行设置，设置好以后注意编译保存下载。
2.程序的编写
3.PID调节
首先在开始菜单中打开PID调节面板，如下图所示：。
S7-300PID控制说明
S7-300的PID控制的方法1、这是一个典型的PID控制系统。
通过模拟量4--20mA的传感器来监视水池的液位，对应PLC的0-27648的工程值，经这个比例转换成水池的液位。
对应的液位是你液位传感器对应的最高量程。
这个值就是PID的反馈值。
阀门调节由量模拟量输出控制阀门调节开度，控制你水池的液位。
2、无法与实际水位对应（读的参数不知道表示什么意思）？在PID调节中有不同的物理量，因此在参数设定中需将其规格化。
参数规格化：1.规格化概念及方法：PID参数中重要的几个变量，给定值，反馈值和输出值都是用0.0~1.0之间的实数表示，因此，需要将模拟输入转换为0.0~1.0的数据，或将0.0~1.0的数据转换为模拟输出，这个过程称为规格化。
规格化的方法：（即变量相对所占整个值域范围内的百分比对应与27648数字量范围内的量）。
对于输入和反馈，执行：变量*100/27648，然后将结果传送到PV-IN和SP-INT，对于输出变量，执行：LMN*27648/100，然后将结果取整传送给PQW即可；2.例：输入参数：SP_INT(给定值）：0--100%的实数。
假定模块的输入变量量程为0-10Mpa,则SP_IN的范围0.0-1.00对应0-10米.可以根据这一比例关系来设置给定值。
例：如给定5.0米SP_INT(给定值）=5.0/(10.0-0.0)*100.0=50.0（50%）PV_IN(过程值，即反馈值）：0--100%的实数。
此值来自与阀门阀位（开度）的相应的压力反馈值。
其范围0.0-1.0对应0-100%.即，当模拟量模板输入为数值为27648时则对应100%（量程的上限），数值为0时则对应0%（量程的下限）。
可以根据这一比例关系来换算PV_IN值。
例：如输入数值为12000时PV_IN(过程值，即反馈值）=12000/27648*100.0=43.403（43.403%）输出参数：当通过PID控制器（FB41）运算后，即得出调节值LMN_PER,该值已转化范围为0-27648的整型数值。
S7-300PID控制说明
S7-300的PID控制的方法1、这是一个典型的PID控制系统。
2、通过模拟量4--20mA的传感器来监视水池的液位，对应PLC的0-27648的工程值，经这个比例转换成水池的液位。
对应的液位是你液位传感器对应的最高量程。
这个值就是PID的反馈值。
3、阀门调节由量模拟量输出控制阀门调节开度，控制你水池的液位。
4、2、无法与实际水位对应（读的参数不知道表示什么意思）5、在PID调节中有不同的物理量，因此在参数设定中需将其规格化。
参数规格化：6、 1.规格化概念及方法：PID参数中重要的几个变量，给定值，反馈值和输出值都是用~之间的实数表示，因此，需要将模拟输入转换为~的数据，或将~的数据转换为模拟输出，这个过程称为规格化。
规格化的方法：（即变量相对所占整个值域范围内的百分比对应与27648数字量范围内的量）。
对于输入和反馈，执行：变量*100/27648，然后将结果传送到PV-IN和SP-INT，对于输出变量，执行：LMN*27648/100，然后将结果取整传送给PQW即可；7、 2.例：8、输入参数：9、SP_INT(给定值）：0--100%的实数。
10、假定模块的输入变量量程为0-10Mpa,则SP_IN的范围对应0-10米.可以根据这一比例关系来设置给定值。
例：如给定米11、SP_INT(给定值）=（50%）12、PV_IN(过程值，即反馈值）：0--100%的实数。
13、此值来自与阀门阀位（开度）的相应的压力反馈值。
其范围对应0-100%.即，当模拟量模板输入为数值为27648时则对应100%（量程的上限），数值为0时则对应0%（量程的下限）。
14、可以根据这一比例关系来换算PV_IN值。
例：如输入数值为12000时15、PV_IN(过程值，即反馈值）=12000/27648*=（%）16、输出参数：17、当通过PID控制器（FB41）运算后，即得出调节值LMN_PER,该值已转化范围为0-27648的整型数值。
西门子S7-300_400PLC的PID调节功能模块的详细说明
Group Topic1Simple PID Controllers for the S7-300/400OverviewThis programming example shows a method for programming a Proportional Integral Derivative (PID) controller on a S7 PLC. The example is already a fully functioning program, needing only for the user to tie the actual inputs and outputs to appropriate variables to be a working controller. This program is suitable for simple PID applications.For complex PID applications, Siemens offers the SIMATIC S7 Standard Control software package, which offers numerous features that this applications tip lacks. These features include alarming, scaling, deadband control, feed-forward control, range limiting, ramp/soak steps, and an integrated scheduler. The Standard Control package includes a Windows-based configuration tool that greatly simplifies configuring and tuning a PID loop.To prepare a user to make these programming changes, the text will explain the basics of the PID controller implemented in the sample code. Below is a brief outline for the rest of this document:1.What does the example program do?2.Where do you use a PID controller?3.Auto Mode vs. Manual Mode4.What does a PID controller do, and how?5.What are the Sample, Gain, Rate, and Reset?6.How is the Error figured?7.How is the Proportional term figured?8.How is the Integral term figured?9.How is the Derivative term figured?10.What if the final Output is too high?11.What should the user add to make the program work for his system?12.Adjusting the Reset, Rate, Gain, Sample time and Mode during run-timePID ExploredWhat does the example program do?示例程序的用途？This programming example is a skeleton program for a true PID controller and, as such, requires that the user make a few additions (i.e. read/write input/output variables) before it is fully functional. Before discussing these, however, let’s get a better feel for what a PID program actually does through a brief example.When do you use a PID controller?Figure 2.1 shows a picture of an example system to which a user might connect a PID controller. The figure shows a water tank sitting atop a hot plate, with a temperature control device for the hot plate and a small, monitored turbine for measuring the rate of the steam flow. This is a system that will work with a PID controller because of the relationship between the two variables: You can directly control the steam flow rate by adjusting the temperature of the hot plate. Figure 2.2 shows how both variables relate to the PID controller.The variable which represents the state of the system being controlled is called the ‘Process Variable.’ In our example above, you can see that the rate at which the steam spins the turbine is a good indicator of the event that we are trying to control: the speed at which the water is being boiled off. The output is the variable which, being altered by the controller, can affect the process variable by different degrees based on its intensity -- By turning the hot plate up, the water boils more quickly, more steam is produced, and the turbine’s speed increases. Therefore, when a variable that accurately reflects the state of the process and an adjustable control which proportionally affects the process variable, then it is possible to use a PID controller. Common systems using PID controllers are air conditioning systems, solution mixing, heaters, etc.Auto Mode vs. Manual Mode自动模式和手动模式There are two settings available on our PID controller. Putting a controller in Manual mode causes the PID loop do nothing, so that the user can directly control the output. The second, Auto, is the mode in which the PID loop is actually controlling the system. For the rest of this text, it will be assumed that the controller is in Auto mode.What does the PID controller do, and how does it do it? PID控制器作些什么？如何去做？Quite simply, a PID controller adjusts the value of its output to try and balance the value of the process variable to a given ‘setpoint.’To calculate the output value for a given instance, the controller finds the value of three different terms (using its user defined Sample time, Gain, Rate, and Reset values along with the calculated Error value): a Proportional term, an Integral term, and a Derivative term.Output = M P + M I + M DFormula 2.1What are the Sample, Gain, Rate, and Reset, and where do they come from?The sample rate is the cycle time (in milliseconds) at which the PID loop recalculates the output. The gain controls the sensitivity of the output calculation by affecting the influence of all the terms. The reset is a time given in milliseconds which is used to increase or decrease the influence of the Integral term in the equation. Finally, the rate value is used to control the influence of the Derivative term in the equation. Each of these values needs to be preset by the user before the PID controller starts.If the user does not want integral action (no I in the PID calculation), then a value of infinity or a value of 0 should be specified for the integral time. If the user does not want derivative action (no D in the PID calculation), then a value of 0 should be specified for the derivative time. If the user does not want proportional action (no P in the PID), then a value of 0 should be specified for the gain (gain is normally a multiplier in the integral and derivative coefficient calculation, but is removed from the coefficient calculation, if gain = 0, to allow I, ID, or D loop control).How is the Error figured? 误差是如何计算的？Error is figured as the difference between the normalized values of the setpoint and the process variable. The controller calculates this value in three steps. The first two steps are to change both the setpoint and the process variable into values that are based on a 0 to 1 (normalized) scale. This is done using the formulae:SP = raw_SP / max_valPV = raw_PV / max_valFormulae 2.2 & 2.3In the above formulae, the raw_SP and raw_PV values are the actual values that come into the controller, and the max_val term is the maximum value that either can take on. For example, ifthe values of raw_SP and raw_PV were being read in as values from 0 to 27,648, then the max_val term would have the value 27,648.After these two values have been calculated, the error term is figured as follows:Error = SP - PVFormula 2.4How is the Proportional term calculated?The proportional term, M P, is calculated using the following equation:M P = Gain * ErrorFormula 2.2Going back to our earlier example with the water tank, the proportional term says that as the speed of the turbine increases further above the setpoint, the heat is decreased proportionally to bring the speed down. As the turbine slows below the setpoint, the heat is increased to proportionally to bring the speed up.How is the Integral Term calculated? 积分项如何计算？The integral term, M I, is calculated using the following equation:M I = Bias + (C I * Error)Formula 2.3In this equation, two new terms are introduced. The first, C I, is the coefficient系数 of the Integral term, and is calculated from the Reset:C I = Gain * (Sample / Reset)Formula 2.4Both the Sample and Reset terms were introduced earlier, but in this equation their uses become apparent. The larger the Reset value is, the less impact the integral term will have onthe output, while larger Sample times give it a bigger influence (Sample time also affects the Derivative term, which will be explained later).The Bias term in Formula 2.3 represents (technically speaking) the area under the curve of a graph plotting the Error vs. time.Abstractly, however, the Bias value (ideally) grows to an output level that keeps the system stable, letting the Proportional and Derivative terms handle any small fluctuations. In relation to our water tank example from earlier, this means that eventually the Bias portion of M I would be the only significant contribution to the final output value, and the M P and M D terms would only be active (non-zero) when a fluctuation occurred.At a time n the equations for M I and the Bias term are:M I,n = Bias n-1 + (C I * Error)Bias n = M I,nFormula 2.5How is the Derivative term calculated?微分项如何计算？The derivative formula for a given time n is calculated with the following equation:M D = C D * (PV n-1 - PV n)Formula 2.6This formula only introduces 1 new term, C D, which is calculated using Formula 2.7.C D = Gain * (Rate / Sample)Formula 2.7The Sample term (which is also used in figuring C I) is the sample time from earlier. In the Derivative term, the Sample time is indirectly proportional to the derivative component, while the Rate is directly proportional.What if the final output value is too high?如果最终输出值太高怎么办？During many processes (such as the water tank example earlier), the Process variable doesn’t respond immediately to a change in the value of the output -- if the water in the tank were ice cold, then even an output of 100% is not going to cause an instantaneous increase in steam flow. Likewise, setting the output to 0% when the water is boiling doesn’t provide an immediate reduction in steam production.Because of this ‘system inertia,’ the output value for a give time could take on a value greater than 100% or less than 0%. In response to this, the PID program implements Output Clamping. If the output is greater than 100%, then it is clamped to 100%. If the output falls lower than 0%, then it is held to 0%.The only problem left to solve lies with the Bias portion of the Integral term. When the output for a system remains at 100% for a long period of time (such as when heating up cold water in our tank from earlier), the integral sum (which the Bias term represents) can grow to extremely large values. This means that when the variable starts responding, the Bias term will be keeping the calculated output well over 100% until it can be wound down. This generally results in the output swinging wildly from one limit to the other, but can be avoided using Bias Clamping. There are a few different types of Bias Clamping, but the only pertinent one here is the one used in the program. There are two different conditions which cause Bias clamping to occur and two formulae as well:If Output > 1Bias = 1 - (M P + M D)Formula 2.8If Output < 0Bias = -(M P + M D)Formula 2.9As the formulae show, when the Output grows to be greater than 1, the value of the Bias is adjusted so that the sum of M P, M D, and the Bias will be 1. Likewise, when the Output slips below 0, the value of the Bias is adjusted so that the above sum will be 0. The adjusted Bias value is then clamped such that its maximum value is 1 and its minimum value is 0.What should be added to make the program work for the system?1. Read in the Process Variable2. Write the Output3. Set the Setpoint4. Adjust the scale for the Input and Setpoint5. Adjust the scale for the Output6. Adjust the Reset, Rate, Gain, and Sample time values.Read in the Process VariableThe Process variable (the variable which accurately reflects the state of the system to be controlled) should be passed to the PV parameter of the function block.Write the OutputThe OUT parameter of the PID loop should be set to the analog output being controlled in the PID function block call.Set the SetpointThe user’s code must pass the Setpoint value to the PID function block via the SP parameter.Adjust the scale for the Process Variable and Setpoint 调整过程值和设定点值。
S7-300 PID用法
用西门子s7_300实现PID控制
在OB35中实现PID控制程序,OB35是一个以固定时间间隔循环执行的组织块，Hardware Config界面里可以设置间隔时间，而这也即是PID的采样时间。
应该注意设置的间隔值比OB35中程序运行时间长，否则会造成系统异常。
P:Kc 增大,系统余差减小,但不能消失.随着Kc 的增大,相应的过渡过程由不振荡变为临界振荡或衰减振荡.
I:积分作用能消除余差.Ti 小表示积分作用强,积分作用越强,过渡过程的振荡越剧烈. D:在比例作用的基础上增加微分作用将使系统的过度过程的振荡程度降低,提高了系统的稳定性.但微分作用不能太强.即Td 不能太大.否则会因反应速度太快引起系统剧烈振荡。
S7-300的PID控制
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用S7-300PLC进行PID控制——功能块FB41的功能及用法介绍
用S7-300PLC进行PID控制——功能块FB41的功能及用法介绍一、控制系统假设图1 液压系统控制框图如图1为液压系统的简单控制框图。
控制方式为使用变频器拖动泵，使系统的实际压力等于设定压力。
本文基于此系统，探讨一下如何用S7-300进行PID控制。
为方便讨论，做以下假定：•· 系统压力的可调范围为：0 – 1MPa；•· 变频器的变频范围为：0 – 50Hz；•· 压力传感器的输入外设地址：PIW272；模拟量输出外设地址为PQW288。
二、FB41简介在STEP7中的库中，有专门用于PID控制的FB块——FB41。
PID控制必须在循环中断中执行，以确保其扫描、执行时间基本固定。
本例中的CPU仅有OB35一个循环中断，因此，要在OB35中调用FB41。
图2 FB41在库中的位置图3 FB41的逻辑图FB41的逻辑如图3所示。
分解介绍如下：•· SP_INT端为给定值，本例中即为给定压力，假设为0.5MPa；即：0.5==>'SP_INT';•· 实际值有两条通路可选：· 当PVPER_ON=0时，PV_IN端的值为实际值，该值通常有FC105转换而来；· 当PVPER_ON=1时，PV_PER端的值为实际的压力值，该值来自AI模块，为压力传感器的反馈值；本例中，我们以PVPER_ON=1时，来说明。
即:1==>'PVPER_ON'、PIW272==>'PV_PER'•· PV_FAC、PV_OFF对应压力的范围，即：1==>'PV_FAC'、0==>'PV_OFF'。
•· PV是根据PV_PER计算出的实际压力值。
具体来说：PV_PER=0时，对应的实际压力为PV_OFF，即0MPa；PV_PER=27648时，对应的实际压力为PV_FAC，即1MPa；PV=PV_PER/27648*(PV_FAC –PV_OFF)，本例中，PV=PV_PER/27648；•· ER为给定值SP_INT和实际值PV的偏差，PID即是基于它进行调节的；•· GAIN、TI、TD分别为比例、积分、微分的系数。
S7-300-PID-使用说明及应用
定时中断组织块OB35西门子S7-300/400有9个定时中断组织块：OB30、OB31、OB32、OB33、OB34、OB35、OB36、OB37、OB38 。
CPU可以定时中断去执行这些模块中的程序，即:每隔一段时间就停止当前的程序，转去执行定时中断组织块中的程序，执行结速后再返回。
相当于单片机的定时中断。
这9个组织块功能相同，你可以选择其中之一使用，区别是它们的中断优先级不同，如果程序中用到了多个定时中断组织块，应设好它们的执行优先级。
S7-300CPU 可用的定时中断组织模块是OB35，在300站点的硬件组态中，打开CPU 属性设置可以看到其它的中断组织块为灰色。
OB35默认的调用时间间隔为100ms 我们可以根据需要更改，定时范围是1-60000毫秒(ms)设置中断时间间隔如下图所示注意：设置的时间必须大于OB35中程序执行所花费的时间。
例如：如果中断时间间隔为50ms而OB35中的程序花费的时间是70ms,那么OB35中的程序还没执行完毕就产生第二次中断，程序就会出错，这显然是我们不想看到的结果。
以现在的技术，让你间隔一小时去月球拿一块石头你能做到吗？？？去月球所用的时间大于去月球的时间间隔，你做不到吧？？？正确设置：中断时间间隔大于OB35中程序执行完毕一次所需的时间使用FB41实现PID控制在自动化领域中常常要用到PID控制，而常规仪表里一个控制器就只能实现一路的PID 控制，如果要现实多路的PID控制成本就会变得非常高，而且不便于我们集中控制与管理。
经过学习西门子S7-300PLC，我们可以使用模块FB41来实现PID控制，FB41就相当于我们常规仪表里的控制器，既然是PID控制器就应该能够设定P、I、D参数。
即：比例度、积分时间、微分时间。
常规仪表的面板上可以更改PID参数，又有手动/自动切换按钮等。
今天我们要做的就是使用S7-300PLC 的FB41来代替常规仪表，如何使用FB41来实现PID控制的呢？？FB41是一个功能块，它所能实现的功能（PID）已经由专业人员设计好，我们只要调用它，并根据我们的需要来更改相应的参数即可使用。
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西门子PLC S7-300PID调试指南
西门子PLC S7-300系列的模块配置灵活，扩展性强，通讯功能强大，为自动化控制系统提供了解决方案。
西门子PLC S7-300的编程软件是STEP7 V5.5，在编程软件中，用户可以通过PID功能块实现PID控制。
本文下面为您介绍一下西门子PLC S7-300PID调试方法，为您在程序调试中提供一些参考。
西门子PLC S7-300系列PLC的PID控制器参数整定的一般方法：PID控制器的参数整定是控制系统设计的核心内容。
它是根据被控过程的特性确定PID控制器的比例系数、积分时间和微分时间的大小。
PID控制器参数整定的方法很多，概括起来有两大类：
一是理论计算整定法。
它主要是依据系统的数学模型，经过理论计算确定控制器参数。
这种方法所得到的计算数据未必可以直接用，还必须通过工程实际进行调整和修改。
二是工程整定方法。
它主要依赖工程经验，直接在控制系统的试验中进行，且方法简单、易于掌握，在工程实际中被广泛采用。
PID控制器参数的工程整定方法，主要有临界比例法、反应曲线法和衰减法。
三种方法各有其特点，其共同点都是通过试验，然后按照工程经验公式对控制器参数进行整定。
但无论采用哪一种方法所得到的控制器参数，都需要在实际运行
中进行最后调整与完善。
现在一般采用的是临界比例法。
利用该方法进行PID控制器参数的整定步骤如下：
(1)首先预选择一个足够短的采样周期让系统工作;
(2)仅加入比例控制环节，直到系统对输入的阶跃响应出现临界振荡，记下这时的比例放大系数和临界振荡周期;
(3)在一定的控制度下通过公式计算得到PID控制器的参数。
PID参数的设定：是靠经验及工艺的熟悉，参考测量值跟踪与设定值曲线，从而调整P\I\D的大小。
比例I/微分D=2，具体值可根据仪表定，再调整比例带P，P过头，到达稳定的时间长，P太短，会震荡，永远也打不到设定要求。
本文介绍了西门子PLC S7-300系列PID调试基本方法，用户可以参照本文提供的内容，对自动化控制系统进行PID调节，并最终达到稳定运行。
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