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Archive 1 |
Proportional - To handle the present, the error is multiplied by a (negative) constant P (for "proportional"), and added to (subtracting error from) the controlled quantity. P is only valid in the band over which a controller's output is proportional to the error of the system. For example, for a heater, a controller with a proportional band of 10 °C and a setpoint of 20 °C would have an output of 100% at 10 °C, 50% at 15 °C and 10% at 19 °C. Note that when the error is zero, a proportional controller's output is zero
This means that when the process variable maches the set point there is no out put from the controller i want to know that if gives 0% out put at when the process variable achieve the set pont position
then it will make a rapid change after some time and again begain to decrease the temprature acording to the process lag
And for pressure loop is it same the proportional band is 100 psi and the set point is 200psi what u think is it possible that when 200 psi achieved it closes the valve 100% then wht will be the correct table for it
INPUT(PSI) OUTPUT(%) 200 0% 150 50% 100 100%
plese clear my concept about this confusion.And its only about proportional controler. I am at initial state learning process your guidence will be very knowledgeful for me.you can also mail me at my email address
Thanks REHAN RIAZ rehanriaz.tech@gmail.com
This page is borked. I tried cleaning it up down to 'Theory', standardizing, etc etc.
I couldn't come up with a good example of cascading PID. I was thinking of a waste wood fed steam boiler, with one PID loop internal to the feed auger VFD + steam pressure and a second PID loop of an external loop controller with a sensor on the stack temperature, but then couldn't figure out how you would feed the output of the second controller into the first if it was already a loop with its own input. What is cascading PID?
Input > Controller > Output=Input > Controller > Output??? Why would you want to do that? Someone clarify?
GarrettSocling 21:07, 10 May 2006 (UTC)
(Answer) In a cascading structure, the controller output of the outer loop is used as the set-point of the inner loop. With y1=plant output used for inner loop, y2=plant output used for outer loop, u1=plant input, r1=set-point of inner loop and r2=set-point of outer loop, the outer controller uses r2-y2 as input (it tries to bring this quantity to 0) and generates u2; the inner controller takes it as set-point r1=u2, using u2-y1 as input (it tries to bring this quantity to 0) and generates u1 which is fed to the plant (for the sake of simplicity, we assume our controllers act on the error between the set-point and the measured plant output). Cascading is used typically when your inner loop is faster than the outer loop: you improve the performance of the inner part by adding a controller to make it more linear, less sensitive to disturbances, etc.; then you design the outer loop by considering the inner loop to be a simple system. For instance, in a car, the inner loop could control the wheel direction with an electrical motor, and the outer loop could control the trajectory of the car on the road. Basically, cascading is a trick to have more parameters to tune and to split the design when a simple PID isn't enough.
Mausy5043 09:17, 18 October 2006 (UTC): The example I like to use is that of a large tank filled with liquid and a jacket used to heat it up. The temperarature of the tank's content is controlled (master loop) by regulating the temperature in the jacket (slave loop).
The other key application of cascade is to allow an intermediate common path to the secondary loop from several influences besides just the influence captured by the primary loop. This allows several loops to target a common secondary setpoint. An example is steam boiler drum level control being influenced by feedwater flow as well as outlet steam pressure.-- Billymac00 16:54, 28 August 2006 (UTC)
Cascade PID control is used widely in the water industry. A good example is controlling a common inlet channel level that feeds multiple filter vessels. the output of a P or PI loop on the inlet channel level is the setpoint to each filter vessel outlet flow PID controller. As a filter is taken offline (or gets blocked) the resulting change in common filter inlet channel level creates a change in setpoint to the remaining on-line filters thereby creating a self compensating system. -- Darran12 11:00, 13 August 2007 (UTC)
Mausy5043 09:39, 18 October 2006 (UTC): I don't understand the first two paragraphs of this chapter:
The PID loop adds positive corrections, removing error from the process's controllable variable (its input).
Differing terms are used in the process control industry: The "process variable" is also called the "process's input" or "controller's output." The process's output is also called the "measurement" or "controller's input."
What we're trying to say here is that the PID loop has an input (e.g. from a measurement device) and an output (e.g. to a controlling device such as a valve or motor). Could someone please simplify these two paragraphs?
Oh my. It's great to have a Loop Tuning section, but it remains kind of useless, because none of the parameters are defined -- Tr, Td, even P. Somewhere in the article, those parameters should appear in an equation describing the PID response. Something like action = P * error + Td * d(error)/dt + ... I don't know how it's conventionally stated, so I won't guess. But whoever put in the otherwise good description of the Ziegler-Nichols method would know. Spiel496 18:43, 12 June 2006 (UTC)
Here is a sample PID interface screen:
The interface should summarize key parameters such as gains, output clamps, direction of action (direct/reverse), setpoint and input and output values.-- Billymac00 18:34, 6 August 2006 (UTC)
The names given to different quantities aren't used in a consistent way. For instance, it is said that the measurement is also called process variable, but later there are input process variables, and one can manipulate some other process variable. And the PID loop is sometimes used for the controller itself; actually, the loop includes the process. It's likely that this confusion also exists in the literature (and perhaps even among a few engineers), but the result is that the article is difficult to understand for someone who doesn't know control. I think we should agree on some simple and explicit terms (e.g. measurement for the process output, controlled value for its input, and desired value for the set-point), use them consistently, and have a separate section where we mention all the other terms the reader may find in books and papers. Engelec 10:21, 18 October 2006 (UTC)
Thanks, whoever recently added the PID loop example diagram, but I think it may be incorrect. It appears to be some variation on a parallel PID control algorithm; however, every control text I have, plus a recent traning course I went on show all three terms (P,I,D) acting on the error for a parallel PID algorithm. In the given diagram, the P and I terms act on the error, and the D term acts acts on the process variable( / measurement / plant output). While I appreciate that in some circumstances, there may be performance advantages to doing it this way, it doesn't appear to be the norm. Additionally, the first paragraph describes a PID controller acting on '...the rate of change of the error signal...' and not '...the rate of change of the plant output...'. The diagram and text should tell the same story. Many industrial PID controllers don't use the parallel algorithm anyway, they use the non-interacting or interacting algorithm. Dave t uk 16:08, 24 October 2006 (UTC)
Is the reasoning that Kd = Dt and follows from dimensional analysis valid (I'm not denying the conclusion, just the stated reasoning)? Dimensional analysis can only show that a certain relationship is possible, it can't actually prove equality. At the very least, dimensional analysis would allow for an arbitrary unitless constant term to be multiplied on either side of the equation.
-- SilverStar 07:26, 25 October 2006 (UTC)
The article has accumulated so many errors and inaccuracies it becomes impossible to manage (just to enumerate a few: sign confusion (PID coefficients are usually positive), interacting mentionned before being defined, wrong definition for the "interacting form" (the parts connected in series are not the same as those of the parallel version), confusion between unstability and oscillations (a system can be unstable and not oscillate, and a nonlinear system can have stable oscillations), meaningless statements (e.g. filter applied to a complex frequency-domain system), etc.). I'd suggest to have a small, clean article on what PID controllers are in their academic version (parallel, controller input = error = setpoint - process output, controller output = process input) with a minimum amount of redundancy with control theory; maybe a section about why it isn't implemented like that; and a separate article on what's found in the industry, jargon, etc. (i.e. everything a beginner shouldn't read before understanding the basics). Engelec 10:52, 25 October 2006 (UTC)
I'd missed this one: the discrete-time version is wrong. Of course, you can implement a PID with three independent coeffients in discrete time (that's how they're done in digital devices like microcontrollers or FPGA). Equation becomes, when using q as the forward-shift operator (see z transform), u(k) for controller output and e(k) for error: u(k) (q-1) = Kp e(k) + Kd (q-1)/q e(k) or u(k)/e(k) = Kp / (q-1) + Kd / q; in other words, a kind of PI controller where Kp is the integral gain and Kd the proportional gain. To get the correct equation, start with u(k)/e(k) = Kp + Ki q/(q-1) + Kd (q-1)/q; then u(k) q (q-1) = (Kp q (q-1) + Ki q^2 + Kd (q-1)^2) e(k), and finally, with the article notations,
Engelec 00:20, 27 October 2006 (UTC)
Is it worth the trouble to fix changes by 129.241.206.68 ("by adding a integration of the average error to the process input" in the I term description)? The previous version wasn't better... Eventually, I'll probably remove all that's wrong, reducing significantly the size of the article. Engelec 15:14, 2 February 2007 (UTC)
I like what Engelec has been doing. Along the same lines as removing the "proportional band" stuff, I suggest we choose just one form for the math. Specifically, do we want
In practice, I prefer the second form, but with and replaced with and , respectively. However, for an encyclopedia article, the first form is probably a less confusing way to introduce the subject. And it matches the figure. Spiel496 04:42, 10 February 2007 (UTC)
Okay, so Crinoid has made a lot of changes, mostly good. Unfortunately, we now have three forms of the main equation in rapid succession, none of which is strictly consistent with the top figure or the section on tuning: Kp+Ti+Td vs. Kp(1+Ti+Td) vs K+Ki+Kd. The display of these different forms is not interesting. Let's just pick one form. I vote for Kp(1+Ti+Td). Are there any objections to this form? It would mean fixing the figure. Spiel496 03:34, 16 February 2007 (UTC)
Feedback controller redirects to this page, obviously PID is not the only feedback compensator ZyMOS
I consider myself an expert in this subject :) So I did a lot of changes to the article. Here are some thoughts.
A lot of confusion in this article arises from the PID's long history. The first implementations were interacting and did not permit the setting of individual gains.
The purely parallel model with separate tunable gains for each part is mostly a mathematical model and can't really be used except in simulators and control engineering education. (Real implementations are digital anyway and most systems include premade PID blocks.)
That's why I think this article should mostly describe the "traditional" model and mathematics that include terms like integral TIME. One interesting fact about using integral TIME is that the integrator element's contribution cannot be made zero with a finite value of Ti. This is a feature of most industrial PID's.
Another interesting fact is that not all non-interacting controllers can be realized in the interacting form. The limiting factor is that Ti must be greater than or equal to 4*Td. If that is satisfied, the parameters can be transformed between the two forms.
This has implications when one tunes a PID with some method and has to input it to a controller that uses the interacting form. The parameters are not even close to being the same value when moving to the other implementation.
Some comments about the interacting/non-interacting (I'll just use I and NI :) forms are also confused. The difference is that the I form is
G = K * ( 1 + Integrator / Ti ) * ( 1+ Derivator * Td )
This is in effect a PD controller(with P gain 1) in series with a (parallel) PI controller.
The parameters of I and NI forms are not interchangeable!
Oh, the point? :-) One MUST know what is the implementation one is working on. The different forms should be properly introduced if they are mentioned at all.
Perhaps another page would be a solution, like... "implementations and extensions to the PID algorithm"? ;)
Crinoid 08:02, 16 February 2007 (UTC)
Should the tuning parts be omitted from this article as well? I think it should be shortened considerably. Ziegler-Nichols tuning rules are given way too much emphasis. The ZN rules are anyway designed for rejection of load disturbances and if used for tuning for step responses, they give too much overshoot (too much sensitivity). Better methods exist.
If PID control is sufficient for the system, even a poorly tuned PID (a stable loop of course) gives results. I remember hearing an estimate that 70% of PID controllers in the industry operate on default settings, and probably the rest just have the "auto-tune" function run once :-)
Crinoid 08:17, 16 February 2007 (UTC)
Boring Friday at work, it seems ;)
About the proportional band, to clarify. It's known that a P controller gives zero output if the error is zero. Thus, no process variable value that requires non-zero input can be reached.
But, if a P controller is used with a bias value (output = K*e + bias), there is one process variable value that can be reached exactly, and that is of course the output corresponding to the bias input.
This is a very powerful control method - first determine the input value that gives the desired output. Then on top of this, implement a P controller with the proportional band set to some reasonable value around the desired output. (Adjusting the bias value is also called reset action.)
The clever thing about PI control is that the integrator part in effect keeps re-setting the bias value for the P controller! So all (reachable) output values can be exactly reached.
Crinoid 08:31, 16 February 2007 (UTC)
"A controller setting of 100% proportional band means that a 100% change of the error signal (setpoint – process variable) will result in 100% change of the output" is another way to say that the proportional term is proportional. The rate "measured in proportional band/minute" was certainly domain-specific. Unless someone older than me can provide better explanations, I'd suggest to remove this section. Engelec 22:43, 21 February 2007 (UTC)
I second the motion. I can't make any sense out of that prose. Spiel496 04:42, 22 February 2007 (UTC)
I was thinking in the "Theory" section (would "PID formula" be better name?) the P, I, and D terms could be better described in terms of a tangible example. A good example would be an automobile cruise control, because many people are familiar with both human- and PID-control of car speed. The P term could be described, along with the limitations of P-only controller. Then the motivation for the I term is to remove steady-state error. Then the D term kind of mimics what a person does -- back off on the accelerator if you are rapidly approaching the target speed. Spiel496 06:46, 24 February 2007 (UTC)
So I have had the last three night shifts to work on the intro to this article. While I am not an expert I am a process operator so I have some experience. I attempted to explain the basic theory and define PID so that someone new to the concept could at least understand it. I ran it by several of my coworkers and they felt my edit was much easier to comprehend than what existed prior. That being said, no hard feelings if it needs to be reverted or so forth. I am going to leave the math and loop tuning to the experts. MDSNYDER 13:51, 5 May 2007 (UTC)
Expert? I've got a PhD Chemical Engineering and 4 years in controller design and implementation, but please judge by the work, not the credentials. I've made minor edits to the intro, major edits to "Controller Basics" and merged the next two (redundant) sections.
With respect to nomenclature and alternative PID forms. Fact is, there is so much variety in common use. It sucks, but there it is. Myself and another guy in the office use different nomenclature. That said, I don't think it is helpful to have all of the alternatives inline in the text because it's just too confusing. I've created a new section "Alternative nomenclature and PID structures" that will contain all of that, keeping the main article consistent and clean. Only got half way so far: we've all got to eat :)
Please post feedback. Even positive feedback is appreciated ;). I'd like to know if I'm on the right track with this. Dhatfield 11:43, 27 July 2007 (UTC)
I have not seen this implemented and I don't know what it means: "# setpoint weighting Setpoint weighting uses different multipliers for the error depending on which element of the controller it is used in. The error in the integral term must be the true control error to avoid steady-state control errors. This affects the controller's setpoint response. These parameters do not affect the response to load disturbances and measurement noise." Can anyone clarify? For now I'll just leave it alone.
I've removed the "{{Expert-portal|Technology|October 2006}}" tag. If you revert (which I will understand completely) please give guidelines for further improvement. Thanks. -- Dhatfield 08:43, 30 July 2007 (UTC)
In the "Alternative Nomenclature..." section there is the statement:
“ | it is possible to modify the integral to such that it does not "record" all historical values of the error signal. There are many possible schemes for performing such modification, such as windowing the signal or applying a decay term to the integral value itself. | ” |
I'll be blunt: I consider this technique to be based on a misunderstanding about what the integral term does. Yes, it does remember that big error from long ago, but the overshoot of the loop since then has canceled out that error. The integral output settles to exactly what it is supposed to be. The infinite memory of the integral term just freaks out some some engineers, and their response is to make modifications like those described in the quote. But the mathematics doesn't point to any benefit. That's my personal belief, anyway. I'd love to excise this section, or present it as "a common misguided technique" but it would be completely original research at this point. Does anyone have a control systems text book that speaks to this? Spiel496 05:42, 15 September 2007 (UTC)
I agree integral windup is a real problem. It arises when the Process Variable is unable to respond linearly to the Manipulated Variable. In Nigelj's example, when the furnace is way below the 1000 C set point, the heater may be saturated at 100W, while the PID loop is requesting something absurd, like 500kW. It would indeed make sense to prevent the Integral from remembering that frustrating period from its past. Does it make sense then to restrict the "clever modifications of the integral" to the section on windup? Even there I don't see the wisdom in "Limiting the time period over which the integral error is calculated", but the other three techniques sound legit. Spiel496 04:28, 18 September 2007 (UTC)
Hi, I think that when using e for the error is somewhat not suitable notation as when learning this coupled with being introduced to laplace transforms at uni. I was under the understanding that this was some expenisional term which as when using laplace occurs a lot so for someone learning this topic it would be easier to note this as E or ε. I do see now that this was denoted as error but still confused me.
I know this may seem perdantic but i feel this is a nessessury change to make the topic (which is great by the way) better.
Thanks Andy (Study Chemical Engineering) —Preceding unsigned comment added by 138.38.152.11 ( talk) 12:22, 20 November 2007 (UTC)
I don't feel that the second block of code in PID_controller#Pseudocode adds much to the article. The content is virtually identical to the first block, except for the absence of the constant dt. Do many others feel this level of implementation detail is warranted? Spiel496 ( talk) 22:56, 27 March 2008 (UTC)
The pseudocode section as it stands is very helpful...it almost solely describes the PID conecpt in less than 30 seconds...and is alot easier to understand than a bunch of mathematics. Thanks to whoever put it there :) — Preceding unsigned comment added by 12.73.190.141 ( talk) 15:16, 31 January 2012 (UTC)
I am trying to add a table of manual loop tuning initial estimates.
The table is useful information for people practically trying to tune a control valve.
This table is relevant to the manual tuning of control valves and thus appropriately placed.
The source article is a hard copy of a single page document issued by Exxon as a starting point for tuning control valves.
The units presented in the table are in SI.
Proportional - dimensionless (-)
Integral - seconds (s)
Derivative - seconds (s)
Is the reference note all that is required to keep the table in place? How do I reference a single page hard copy? Are there philosophical objections to its inclusion based on the fact it is for practical rather than theoretical application?
I will revert the document to include the table once again. But if undoing the change could you please respond here. —Preceding
unsigned comment added by
203.47.182.117 (
talk)
06:39, 11 June 2008 (UTC)
203.47.182.117, a few comments to get you started (I'm assuming you are new around here). First, you are congratulated for being bold. If you plan to continue editing, here are some tips:
Regarding recent edits to the Pseudocode, with the removal of dt. In order for a loop of this nature to funciton, it would have to be driven such that the loop executes every dt units of time *as well as* incorporating the units of time into the tuning parameters. This is not consistent with the rest of the article, as the tuning parameter is now not just system dependant, but also dependent upon your loop's update time period.
Examples:
and the tuning parameters are" -- this form does not match the new pseudocode either. User A1 ( talk) 11:01, 14 October 2008 (UTC)
Now it's ok, but remember that this type of struct is ideal PID, change "Here is a simple software loop that implements the PID algorithm:" to "Here is a simple software loop that implements a Digital Ideal PID algorithm:" —Preceding
unsigned comment added by
189.19.196.155 (
talk)
16:20, 14 October 2008 (UTC)
Bold has been used since the article began in August 2006. Dicklyon ( talk), I don't know why you think this is no longer appropriate. I think it made the article easier to read. Please put it back. Robert - Northern VA ( talk) 20:08, 30 October 2008 (UTC)
On Oct 14 [1], the article was modified to indicate that the I term controls the long term offset and that D controls the rise time (as described in the article). This agrees with what was in the article Jan 2008 [2]. For some reason Dicklyon ( talk) removed this edit. I don't understand why. Robert - Northern VA ( talk) 20:23, 30 October 2008 (UTC)
Old modifications:
This's proportional only! :
Dead Bands:
if(absolute(error) <= dead_band) then: integral_sum don't change else: integral_sum = integral_sum + error
if(absolute(proportional_error) <= dead_band) then: proportional term = 0 else: proportional term = proportional_error * proportional gain
if(absolute(derivative value) <= dead_band) then: derivative term = 0 else: derivative term = derivative value * derivative gain
New modifications, Derivative modifications:
Integral modifications:
integral_sum = integral_sum - error_value
or proportional to saturation value. (anti windup sum showed on books)
integral_sum = integral_sum - (pre saturation output filter - saturated output)
saturation filter function:
if(value>max) then: output = max elseif(value<min) then: output = min else output = value
Others modifications, i didn't found the name but are used:
Conditional integral sum
if absolute(derivative_value) > pre_determined_value then: integral = integral - error
if (error > x) then: integral_error=x else if (error < y) then: integral_error=y else: integral_error=error integral_sum = integral_sum + integral_error
The following associations were recently added
I don't know where these come from and I suggest removing them unless a reference is provided. Q Science ( talk) 15:22, 5 January 2009 (UTC)
I think it should be:
(unsigned comment by 89.133.22.172)
user:User A1, I thought the excel spreadsheet was pretty cool. It even allows random noise to be added. I assume that you deleted it because it broke one of the wikipedia rules, but isn't there some way that it can be added? Robert - Northern VA ( talk) 07:08, 10 February 2009 (UTC)
A short piece of scilab or matlab psuedocode would be more appropriate for this task. Furthermore, there are technical issues with their method.
In total, these issues, as well as the WP:EL guidelines prompted me to remove the article, as it is a non-authoritarian source. User A1 ( talk) 10:36, 10 February 2009 (UTC)
the Kp plot is incorrect —Preceding unsigned comment added by 192.158.61.142 ( talk) 21:00, 8 June 2009 (UTC)
To make the plots, the contributor ( Skorkmaz) had to assume some example process, and we don't know its characteristics. Perhaps that process is really atypical. For instance, if the process has no high frequency poles, then there won't be any onset of ringing as Kp is increased. The question is, what process characteristics would serve as a good example? I think we'd want to have one pole much lower than the desired closed loop response -- that would mimic the situation in thermal control where the process acts almost like an integrator. Then another pole just above the loop response, in order to make things ring if the gain is set too high. Maybe we'd need two up there to demonstrate the benefit of the derivative term. Does anyone have more specific suggestions? Spiel496 ( talk) 19:33, 29 January 2010 (UTC)
I'm not an expert, but trying to learn PID. It seems to me that the graph for demonstrating Kp should show a "typical" example where a large Kp causes more overshoot, and a small Kp causes less overshoot. While there may be atypical processes as Spiel above indicates, the purpose of an introductory article should be to demonstrate the basic principles using a typical process as a basis. I think that exchanging the curves for Kp=0.5 and Kp=2 would be more illustrative to a beginner. Or have I missed the point completely? —Preceding unsigned comment added by 67.169.6.121 ( talk) 17:24, 3 March 2011 (UTC)
Should there be reference to the improved Ziegler-Nichols method? I think it wasn't much just modified equations for the Ki and Kd. I'm not an expert so I won't make an edit. We just used it a lot more often in my undergrad degree.
Further I seem to remember another manual technique for tuning that was more involved than that mentioned and converged to an optimen quicker. There was an actual process to go through and you tended to get the "correct" result in two or three iternations after starting with Ziegler-nichols method's. —Preceding unsigned comment added by 119.224.62.103 ( talk) 03:18, 20 July 2009 (UTC)
Is there an article on this?
http://users.erols.com/jyavins/servo.html —Preceding unsigned comment added by 71.167.65.207 ( talk) 02:11, 15 September 2009 (UTC)
There's also IMC tuning (internal model control)...Matlab toolbox has this option-- Billymac00 ( talk) 04:45, 3 February 2010 (UTC)
Had a phone conversation this morning, Tuesday May 11th, 2010, with Honeywell's technical support line at 1-800-468-1502. Representative from Honeywell claimed that what the industry calls PID, _THEY_ call either "Adaptive Intelligent Response" (A.I.R.) or "Smart Response". Also, it's included in every programmable thermostat they sell. Yea, I know, this trivia doesn't fit inside the PID Controller article, but I figured I'd toss it out there in case SOMEONE knows a relevant place to put it.
LP-mn (
talk)
15:03, 11 May 2010 (UTC)
I disagree this is unnecessary complication. It is necessary, because saying that the water valve position is the MV is incorrect. We go to the equation in the article MV=P(e)+I(e)+D(e), and let's for the time being ignore the I and D terms. So we have MV=P(e), which from the aritcle is MV=K_p*e(t). Now we say the MV is the absolute valve position. So let's say we want to set the water temp to 35 degrees, and we have the hot water valve open at say 15%, and the water temp in the water bath is indeed 35 degrees. So e(t)=0. So this would mean at 35 degrees MV, which is the absolute water valve position and has a value of 15% opening at 35 degrees, is zero. 15% opening on the hot water valve equals a MV of zero. Now we want to change the water temp to 55 degrees, so obviously we need to turn the water valve to open more. However if we use the definition that MV=K_p*e(t) then when the water temp is indeed 55 degrees, e(t) is zero and MV has to be zero again according to MV=K_p*e(t). If MV is the absolute water valve position that means the water valve is also only opening at 15% for a water temp of 55 degrees. This doesn't make sense.
What MV is how much corrective action we apply. We have error in the system, we apply more corrective action. The effect of the corrective action is that it changes something in the system. So in the water valve example, the corrective action is turning the valve, not the absolute position of the valve itself. 122.57.201.57 ( talk) 13:36, 27 June 2010 (UTC)
The block diagram shown in the corner is of a style commonly used in control theory, and I believe it comes from diagrams describing analog computers and some electronic signal processing (or at least, the same style of diagram turns up in those places). However, the name "Block Diagram", is used by many disciplines to mean many things, it gets used in control theory to mean this specific type of diagram where the arrows represent signal flow and the blocks represent processing stages, also with the summing junctions and the Sigma symbol in the junction. I can't find a wikipedia page specifically describing the type of block diagram used by control theory, nor can I find a precise name to distinguish this type of diagram from the more generic concept. In partial answer to my own question, there's a category on commons Category:Control_theory_block_diagrams which probably should have a companion wiki page Control theory block diagram and maybe also related to Function block diagram but not exactly.
The plots in this section are essentially meaningless, since there is no explanation for how PV is related to u(t). Certainly, the generation of the plots required some relation between these terms, and without it explicitly defined, the reader is left confused. Whoever made those plots should fill in the details. —Preceding unsigned comment added by 84.108.63.99 ( talk) 05:32, 28 April 2011 (UTC)
Hello,
For the Proportional Term, I think it's wrong in the graph of "Change of response for varying Kp". The black curve with smaller oscillation should have a smaller proportional gain Kp. The red curve with bigger oscillation should have a bigger proportional gain Kp. But in the graph, it seems wrong way round. So by my understanding, the black curve should have Kp=0.5 and the red curve should have Kp=2. Am I right?
Many Thanks,
Li
The page has it correct. A higher proportional gain will increase response time. Notice how the black curve approaches the command at a faster rate then the others.
On the other hand the red curve, with the smallest gain out of the 3, has the slowest response and thus the largest overshoot.
This is an archive of past discussions. Do not edit the contents of this page. If you wish to start a new discussion or revive an old one, please do so on the current talk page. |
Archive 1 |
Proportional - To handle the present, the error is multiplied by a (negative) constant P (for "proportional"), and added to (subtracting error from) the controlled quantity. P is only valid in the band over which a controller's output is proportional to the error of the system. For example, for a heater, a controller with a proportional band of 10 °C and a setpoint of 20 °C would have an output of 100% at 10 °C, 50% at 15 °C and 10% at 19 °C. Note that when the error is zero, a proportional controller's output is zero
This means that when the process variable maches the set point there is no out put from the controller i want to know that if gives 0% out put at when the process variable achieve the set pont position
then it will make a rapid change after some time and again begain to decrease the temprature acording to the process lag
And for pressure loop is it same the proportional band is 100 psi and the set point is 200psi what u think is it possible that when 200 psi achieved it closes the valve 100% then wht will be the correct table for it
INPUT(PSI) OUTPUT(%) 200 0% 150 50% 100 100%
plese clear my concept about this confusion.And its only about proportional controler. I am at initial state learning process your guidence will be very knowledgeful for me.you can also mail me at my email address
Thanks REHAN RIAZ rehanriaz.tech@gmail.com
This page is borked. I tried cleaning it up down to 'Theory', standardizing, etc etc.
I couldn't come up with a good example of cascading PID. I was thinking of a waste wood fed steam boiler, with one PID loop internal to the feed auger VFD + steam pressure and a second PID loop of an external loop controller with a sensor on the stack temperature, but then couldn't figure out how you would feed the output of the second controller into the first if it was already a loop with its own input. What is cascading PID?
Input > Controller > Output=Input > Controller > Output??? Why would you want to do that? Someone clarify?
GarrettSocling 21:07, 10 May 2006 (UTC)
(Answer) In a cascading structure, the controller output of the outer loop is used as the set-point of the inner loop. With y1=plant output used for inner loop, y2=plant output used for outer loop, u1=plant input, r1=set-point of inner loop and r2=set-point of outer loop, the outer controller uses r2-y2 as input (it tries to bring this quantity to 0) and generates u2; the inner controller takes it as set-point r1=u2, using u2-y1 as input (it tries to bring this quantity to 0) and generates u1 which is fed to the plant (for the sake of simplicity, we assume our controllers act on the error between the set-point and the measured plant output). Cascading is used typically when your inner loop is faster than the outer loop: you improve the performance of the inner part by adding a controller to make it more linear, less sensitive to disturbances, etc.; then you design the outer loop by considering the inner loop to be a simple system. For instance, in a car, the inner loop could control the wheel direction with an electrical motor, and the outer loop could control the trajectory of the car on the road. Basically, cascading is a trick to have more parameters to tune and to split the design when a simple PID isn't enough.
Mausy5043 09:17, 18 October 2006 (UTC): The example I like to use is that of a large tank filled with liquid and a jacket used to heat it up. The temperarature of the tank's content is controlled (master loop) by regulating the temperature in the jacket (slave loop).
The other key application of cascade is to allow an intermediate common path to the secondary loop from several influences besides just the influence captured by the primary loop. This allows several loops to target a common secondary setpoint. An example is steam boiler drum level control being influenced by feedwater flow as well as outlet steam pressure.-- Billymac00 16:54, 28 August 2006 (UTC)
Cascade PID control is used widely in the water industry. A good example is controlling a common inlet channel level that feeds multiple filter vessels. the output of a P or PI loop on the inlet channel level is the setpoint to each filter vessel outlet flow PID controller. As a filter is taken offline (or gets blocked) the resulting change in common filter inlet channel level creates a change in setpoint to the remaining on-line filters thereby creating a self compensating system. -- Darran12 11:00, 13 August 2007 (UTC)
Mausy5043 09:39, 18 October 2006 (UTC): I don't understand the first two paragraphs of this chapter:
The PID loop adds positive corrections, removing error from the process's controllable variable (its input).
Differing terms are used in the process control industry: The "process variable" is also called the "process's input" or "controller's output." The process's output is also called the "measurement" or "controller's input."
What we're trying to say here is that the PID loop has an input (e.g. from a measurement device) and an output (e.g. to a controlling device such as a valve or motor). Could someone please simplify these two paragraphs?
Oh my. It's great to have a Loop Tuning section, but it remains kind of useless, because none of the parameters are defined -- Tr, Td, even P. Somewhere in the article, those parameters should appear in an equation describing the PID response. Something like action = P * error + Td * d(error)/dt + ... I don't know how it's conventionally stated, so I won't guess. But whoever put in the otherwise good description of the Ziegler-Nichols method would know. Spiel496 18:43, 12 June 2006 (UTC)
Here is a sample PID interface screen:
The interface should summarize key parameters such as gains, output clamps, direction of action (direct/reverse), setpoint and input and output values.-- Billymac00 18:34, 6 August 2006 (UTC)
The names given to different quantities aren't used in a consistent way. For instance, it is said that the measurement is also called process variable, but later there are input process variables, and one can manipulate some other process variable. And the PID loop is sometimes used for the controller itself; actually, the loop includes the process. It's likely that this confusion also exists in the literature (and perhaps even among a few engineers), but the result is that the article is difficult to understand for someone who doesn't know control. I think we should agree on some simple and explicit terms (e.g. measurement for the process output, controlled value for its input, and desired value for the set-point), use them consistently, and have a separate section where we mention all the other terms the reader may find in books and papers. Engelec 10:21, 18 October 2006 (UTC)
Thanks, whoever recently added the PID loop example diagram, but I think it may be incorrect. It appears to be some variation on a parallel PID control algorithm; however, every control text I have, plus a recent traning course I went on show all three terms (P,I,D) acting on the error for a parallel PID algorithm. In the given diagram, the P and I terms act on the error, and the D term acts acts on the process variable( / measurement / plant output). While I appreciate that in some circumstances, there may be performance advantages to doing it this way, it doesn't appear to be the norm. Additionally, the first paragraph describes a PID controller acting on '...the rate of change of the error signal...' and not '...the rate of change of the plant output...'. The diagram and text should tell the same story. Many industrial PID controllers don't use the parallel algorithm anyway, they use the non-interacting or interacting algorithm. Dave t uk 16:08, 24 October 2006 (UTC)
Is the reasoning that Kd = Dt and follows from dimensional analysis valid (I'm not denying the conclusion, just the stated reasoning)? Dimensional analysis can only show that a certain relationship is possible, it can't actually prove equality. At the very least, dimensional analysis would allow for an arbitrary unitless constant term to be multiplied on either side of the equation.
-- SilverStar 07:26, 25 October 2006 (UTC)
The article has accumulated so many errors and inaccuracies it becomes impossible to manage (just to enumerate a few: sign confusion (PID coefficients are usually positive), interacting mentionned before being defined, wrong definition for the "interacting form" (the parts connected in series are not the same as those of the parallel version), confusion between unstability and oscillations (a system can be unstable and not oscillate, and a nonlinear system can have stable oscillations), meaningless statements (e.g. filter applied to a complex frequency-domain system), etc.). I'd suggest to have a small, clean article on what PID controllers are in their academic version (parallel, controller input = error = setpoint - process output, controller output = process input) with a minimum amount of redundancy with control theory; maybe a section about why it isn't implemented like that; and a separate article on what's found in the industry, jargon, etc. (i.e. everything a beginner shouldn't read before understanding the basics). Engelec 10:52, 25 October 2006 (UTC)
I'd missed this one: the discrete-time version is wrong. Of course, you can implement a PID with three independent coeffients in discrete time (that's how they're done in digital devices like microcontrollers or FPGA). Equation becomes, when using q as the forward-shift operator (see z transform), u(k) for controller output and e(k) for error: u(k) (q-1) = Kp e(k) + Kd (q-1)/q e(k) or u(k)/e(k) = Kp / (q-1) + Kd / q; in other words, a kind of PI controller where Kp is the integral gain and Kd the proportional gain. To get the correct equation, start with u(k)/e(k) = Kp + Ki q/(q-1) + Kd (q-1)/q; then u(k) q (q-1) = (Kp q (q-1) + Ki q^2 + Kd (q-1)^2) e(k), and finally, with the article notations,
Engelec 00:20, 27 October 2006 (UTC)
Is it worth the trouble to fix changes by 129.241.206.68 ("by adding a integration of the average error to the process input" in the I term description)? The previous version wasn't better... Eventually, I'll probably remove all that's wrong, reducing significantly the size of the article. Engelec 15:14, 2 February 2007 (UTC)
I like what Engelec has been doing. Along the same lines as removing the "proportional band" stuff, I suggest we choose just one form for the math. Specifically, do we want
In practice, I prefer the second form, but with and replaced with and , respectively. However, for an encyclopedia article, the first form is probably a less confusing way to introduce the subject. And it matches the figure. Spiel496 04:42, 10 February 2007 (UTC)
Okay, so Crinoid has made a lot of changes, mostly good. Unfortunately, we now have three forms of the main equation in rapid succession, none of which is strictly consistent with the top figure or the section on tuning: Kp+Ti+Td vs. Kp(1+Ti+Td) vs K+Ki+Kd. The display of these different forms is not interesting. Let's just pick one form. I vote for Kp(1+Ti+Td). Are there any objections to this form? It would mean fixing the figure. Spiel496 03:34, 16 February 2007 (UTC)
Feedback controller redirects to this page, obviously PID is not the only feedback compensator ZyMOS
I consider myself an expert in this subject :) So I did a lot of changes to the article. Here are some thoughts.
A lot of confusion in this article arises from the PID's long history. The first implementations were interacting and did not permit the setting of individual gains.
The purely parallel model with separate tunable gains for each part is mostly a mathematical model and can't really be used except in simulators and control engineering education. (Real implementations are digital anyway and most systems include premade PID blocks.)
That's why I think this article should mostly describe the "traditional" model and mathematics that include terms like integral TIME. One interesting fact about using integral TIME is that the integrator element's contribution cannot be made zero with a finite value of Ti. This is a feature of most industrial PID's.
Another interesting fact is that not all non-interacting controllers can be realized in the interacting form. The limiting factor is that Ti must be greater than or equal to 4*Td. If that is satisfied, the parameters can be transformed between the two forms.
This has implications when one tunes a PID with some method and has to input it to a controller that uses the interacting form. The parameters are not even close to being the same value when moving to the other implementation.
Some comments about the interacting/non-interacting (I'll just use I and NI :) forms are also confused. The difference is that the I form is
G = K * ( 1 + Integrator / Ti ) * ( 1+ Derivator * Td )
This is in effect a PD controller(with P gain 1) in series with a (parallel) PI controller.
The parameters of I and NI forms are not interchangeable!
Oh, the point? :-) One MUST know what is the implementation one is working on. The different forms should be properly introduced if they are mentioned at all.
Perhaps another page would be a solution, like... "implementations and extensions to the PID algorithm"? ;)
Crinoid 08:02, 16 February 2007 (UTC)
Should the tuning parts be omitted from this article as well? I think it should be shortened considerably. Ziegler-Nichols tuning rules are given way too much emphasis. The ZN rules are anyway designed for rejection of load disturbances and if used for tuning for step responses, they give too much overshoot (too much sensitivity). Better methods exist.
If PID control is sufficient for the system, even a poorly tuned PID (a stable loop of course) gives results. I remember hearing an estimate that 70% of PID controllers in the industry operate on default settings, and probably the rest just have the "auto-tune" function run once :-)
Crinoid 08:17, 16 February 2007 (UTC)
Boring Friday at work, it seems ;)
About the proportional band, to clarify. It's known that a P controller gives zero output if the error is zero. Thus, no process variable value that requires non-zero input can be reached.
But, if a P controller is used with a bias value (output = K*e + bias), there is one process variable value that can be reached exactly, and that is of course the output corresponding to the bias input.
This is a very powerful control method - first determine the input value that gives the desired output. Then on top of this, implement a P controller with the proportional band set to some reasonable value around the desired output. (Adjusting the bias value is also called reset action.)
The clever thing about PI control is that the integrator part in effect keeps re-setting the bias value for the P controller! So all (reachable) output values can be exactly reached.
Crinoid 08:31, 16 February 2007 (UTC)
"A controller setting of 100% proportional band means that a 100% change of the error signal (setpoint – process variable) will result in 100% change of the output" is another way to say that the proportional term is proportional. The rate "measured in proportional band/minute" was certainly domain-specific. Unless someone older than me can provide better explanations, I'd suggest to remove this section. Engelec 22:43, 21 February 2007 (UTC)
I second the motion. I can't make any sense out of that prose. Spiel496 04:42, 22 February 2007 (UTC)
I was thinking in the "Theory" section (would "PID formula" be better name?) the P, I, and D terms could be better described in terms of a tangible example. A good example would be an automobile cruise control, because many people are familiar with both human- and PID-control of car speed. The P term could be described, along with the limitations of P-only controller. Then the motivation for the I term is to remove steady-state error. Then the D term kind of mimics what a person does -- back off on the accelerator if you are rapidly approaching the target speed. Spiel496 06:46, 24 February 2007 (UTC)
So I have had the last three night shifts to work on the intro to this article. While I am not an expert I am a process operator so I have some experience. I attempted to explain the basic theory and define PID so that someone new to the concept could at least understand it. I ran it by several of my coworkers and they felt my edit was much easier to comprehend than what existed prior. That being said, no hard feelings if it needs to be reverted or so forth. I am going to leave the math and loop tuning to the experts. MDSNYDER 13:51, 5 May 2007 (UTC)
Expert? I've got a PhD Chemical Engineering and 4 years in controller design and implementation, but please judge by the work, not the credentials. I've made minor edits to the intro, major edits to "Controller Basics" and merged the next two (redundant) sections.
With respect to nomenclature and alternative PID forms. Fact is, there is so much variety in common use. It sucks, but there it is. Myself and another guy in the office use different nomenclature. That said, I don't think it is helpful to have all of the alternatives inline in the text because it's just too confusing. I've created a new section "Alternative nomenclature and PID structures" that will contain all of that, keeping the main article consistent and clean. Only got half way so far: we've all got to eat :)
Please post feedback. Even positive feedback is appreciated ;). I'd like to know if I'm on the right track with this. Dhatfield 11:43, 27 July 2007 (UTC)
I have not seen this implemented and I don't know what it means: "# setpoint weighting Setpoint weighting uses different multipliers for the error depending on which element of the controller it is used in. The error in the integral term must be the true control error to avoid steady-state control errors. This affects the controller's setpoint response. These parameters do not affect the response to load disturbances and measurement noise." Can anyone clarify? For now I'll just leave it alone.
I've removed the "{{Expert-portal|Technology|October 2006}}" tag. If you revert (which I will understand completely) please give guidelines for further improvement. Thanks. -- Dhatfield 08:43, 30 July 2007 (UTC)
In the "Alternative Nomenclature..." section there is the statement:
“ | it is possible to modify the integral to such that it does not "record" all historical values of the error signal. There are many possible schemes for performing such modification, such as windowing the signal or applying a decay term to the integral value itself. | ” |
I'll be blunt: I consider this technique to be based on a misunderstanding about what the integral term does. Yes, it does remember that big error from long ago, but the overshoot of the loop since then has canceled out that error. The integral output settles to exactly what it is supposed to be. The infinite memory of the integral term just freaks out some some engineers, and their response is to make modifications like those described in the quote. But the mathematics doesn't point to any benefit. That's my personal belief, anyway. I'd love to excise this section, or present it as "a common misguided technique" but it would be completely original research at this point. Does anyone have a control systems text book that speaks to this? Spiel496 05:42, 15 September 2007 (UTC)
I agree integral windup is a real problem. It arises when the Process Variable is unable to respond linearly to the Manipulated Variable. In Nigelj's example, when the furnace is way below the 1000 C set point, the heater may be saturated at 100W, while the PID loop is requesting something absurd, like 500kW. It would indeed make sense to prevent the Integral from remembering that frustrating period from its past. Does it make sense then to restrict the "clever modifications of the integral" to the section on windup? Even there I don't see the wisdom in "Limiting the time period over which the integral error is calculated", but the other three techniques sound legit. Spiel496 04:28, 18 September 2007 (UTC)
Hi, I think that when using e for the error is somewhat not suitable notation as when learning this coupled with being introduced to laplace transforms at uni. I was under the understanding that this was some expenisional term which as when using laplace occurs a lot so for someone learning this topic it would be easier to note this as E or ε. I do see now that this was denoted as error but still confused me.
I know this may seem perdantic but i feel this is a nessessury change to make the topic (which is great by the way) better.
Thanks Andy (Study Chemical Engineering) —Preceding unsigned comment added by 138.38.152.11 ( talk) 12:22, 20 November 2007 (UTC)
I don't feel that the second block of code in PID_controller#Pseudocode adds much to the article. The content is virtually identical to the first block, except for the absence of the constant dt. Do many others feel this level of implementation detail is warranted? Spiel496 ( talk) 22:56, 27 March 2008 (UTC)
The pseudocode section as it stands is very helpful...it almost solely describes the PID conecpt in less than 30 seconds...and is alot easier to understand than a bunch of mathematics. Thanks to whoever put it there :) — Preceding unsigned comment added by 12.73.190.141 ( talk) 15:16, 31 January 2012 (UTC)
I am trying to add a table of manual loop tuning initial estimates.
The table is useful information for people practically trying to tune a control valve.
This table is relevant to the manual tuning of control valves and thus appropriately placed.
The source article is a hard copy of a single page document issued by Exxon as a starting point for tuning control valves.
The units presented in the table are in SI.
Proportional - dimensionless (-)
Integral - seconds (s)
Derivative - seconds (s)
Is the reference note all that is required to keep the table in place? How do I reference a single page hard copy? Are there philosophical objections to its inclusion based on the fact it is for practical rather than theoretical application?
I will revert the document to include the table once again. But if undoing the change could you please respond here. —Preceding
unsigned comment added by
203.47.182.117 (
talk)
06:39, 11 June 2008 (UTC)
203.47.182.117, a few comments to get you started (I'm assuming you are new around here). First, you are congratulated for being bold. If you plan to continue editing, here are some tips:
Regarding recent edits to the Pseudocode, with the removal of dt. In order for a loop of this nature to funciton, it would have to be driven such that the loop executes every dt units of time *as well as* incorporating the units of time into the tuning parameters. This is not consistent with the rest of the article, as the tuning parameter is now not just system dependant, but also dependent upon your loop's update time period.
Examples:
and the tuning parameters are" -- this form does not match the new pseudocode either. User A1 ( talk) 11:01, 14 October 2008 (UTC)
Now it's ok, but remember that this type of struct is ideal PID, change "Here is a simple software loop that implements the PID algorithm:" to "Here is a simple software loop that implements a Digital Ideal PID algorithm:" —Preceding
unsigned comment added by
189.19.196.155 (
talk)
16:20, 14 October 2008 (UTC)
Bold has been used since the article began in August 2006. Dicklyon ( talk), I don't know why you think this is no longer appropriate. I think it made the article easier to read. Please put it back. Robert - Northern VA ( talk) 20:08, 30 October 2008 (UTC)
On Oct 14 [1], the article was modified to indicate that the I term controls the long term offset and that D controls the rise time (as described in the article). This agrees with what was in the article Jan 2008 [2]. For some reason Dicklyon ( talk) removed this edit. I don't understand why. Robert - Northern VA ( talk) 20:23, 30 October 2008 (UTC)
Old modifications:
This's proportional only! :
Dead Bands:
if(absolute(error) <= dead_band) then: integral_sum don't change else: integral_sum = integral_sum + error
if(absolute(proportional_error) <= dead_band) then: proportional term = 0 else: proportional term = proportional_error * proportional gain
if(absolute(derivative value) <= dead_band) then: derivative term = 0 else: derivative term = derivative value * derivative gain
New modifications, Derivative modifications:
Integral modifications:
integral_sum = integral_sum - error_value
or proportional to saturation value. (anti windup sum showed on books)
integral_sum = integral_sum - (pre saturation output filter - saturated output)
saturation filter function:
if(value>max) then: output = max elseif(value<min) then: output = min else output = value
Others modifications, i didn't found the name but are used:
Conditional integral sum
if absolute(derivative_value) > pre_determined_value then: integral = integral - error
if (error > x) then: integral_error=x else if (error < y) then: integral_error=y else: integral_error=error integral_sum = integral_sum + integral_error
The following associations were recently added
I don't know where these come from and I suggest removing them unless a reference is provided. Q Science ( talk) 15:22, 5 January 2009 (UTC)
I think it should be:
(unsigned comment by 89.133.22.172)
user:User A1, I thought the excel spreadsheet was pretty cool. It even allows random noise to be added. I assume that you deleted it because it broke one of the wikipedia rules, but isn't there some way that it can be added? Robert - Northern VA ( talk) 07:08, 10 February 2009 (UTC)
A short piece of scilab or matlab psuedocode would be more appropriate for this task. Furthermore, there are technical issues with their method.
In total, these issues, as well as the WP:EL guidelines prompted me to remove the article, as it is a non-authoritarian source. User A1 ( talk) 10:36, 10 February 2009 (UTC)
the Kp plot is incorrect —Preceding unsigned comment added by 192.158.61.142 ( talk) 21:00, 8 June 2009 (UTC)
To make the plots, the contributor ( Skorkmaz) had to assume some example process, and we don't know its characteristics. Perhaps that process is really atypical. For instance, if the process has no high frequency poles, then there won't be any onset of ringing as Kp is increased. The question is, what process characteristics would serve as a good example? I think we'd want to have one pole much lower than the desired closed loop response -- that would mimic the situation in thermal control where the process acts almost like an integrator. Then another pole just above the loop response, in order to make things ring if the gain is set too high. Maybe we'd need two up there to demonstrate the benefit of the derivative term. Does anyone have more specific suggestions? Spiel496 ( talk) 19:33, 29 January 2010 (UTC)
I'm not an expert, but trying to learn PID. It seems to me that the graph for demonstrating Kp should show a "typical" example where a large Kp causes more overshoot, and a small Kp causes less overshoot. While there may be atypical processes as Spiel above indicates, the purpose of an introductory article should be to demonstrate the basic principles using a typical process as a basis. I think that exchanging the curves for Kp=0.5 and Kp=2 would be more illustrative to a beginner. Or have I missed the point completely? —Preceding unsigned comment added by 67.169.6.121 ( talk) 17:24, 3 March 2011 (UTC)
Should there be reference to the improved Ziegler-Nichols method? I think it wasn't much just modified equations for the Ki and Kd. I'm not an expert so I won't make an edit. We just used it a lot more often in my undergrad degree.
Further I seem to remember another manual technique for tuning that was more involved than that mentioned and converged to an optimen quicker. There was an actual process to go through and you tended to get the "correct" result in two or three iternations after starting with Ziegler-nichols method's. —Preceding unsigned comment added by 119.224.62.103 ( talk) 03:18, 20 July 2009 (UTC)
Is there an article on this?
http://users.erols.com/jyavins/servo.html —Preceding unsigned comment added by 71.167.65.207 ( talk) 02:11, 15 September 2009 (UTC)
There's also IMC tuning (internal model control)...Matlab toolbox has this option-- Billymac00 ( talk) 04:45, 3 February 2010 (UTC)
Had a phone conversation this morning, Tuesday May 11th, 2010, with Honeywell's technical support line at 1-800-468-1502. Representative from Honeywell claimed that what the industry calls PID, _THEY_ call either "Adaptive Intelligent Response" (A.I.R.) or "Smart Response". Also, it's included in every programmable thermostat they sell. Yea, I know, this trivia doesn't fit inside the PID Controller article, but I figured I'd toss it out there in case SOMEONE knows a relevant place to put it.
LP-mn (
talk)
15:03, 11 May 2010 (UTC)
I disagree this is unnecessary complication. It is necessary, because saying that the water valve position is the MV is incorrect. We go to the equation in the article MV=P(e)+I(e)+D(e), and let's for the time being ignore the I and D terms. So we have MV=P(e), which from the aritcle is MV=K_p*e(t). Now we say the MV is the absolute valve position. So let's say we want to set the water temp to 35 degrees, and we have the hot water valve open at say 15%, and the water temp in the water bath is indeed 35 degrees. So e(t)=0. So this would mean at 35 degrees MV, which is the absolute water valve position and has a value of 15% opening at 35 degrees, is zero. 15% opening on the hot water valve equals a MV of zero. Now we want to change the water temp to 55 degrees, so obviously we need to turn the water valve to open more. However if we use the definition that MV=K_p*e(t) then when the water temp is indeed 55 degrees, e(t) is zero and MV has to be zero again according to MV=K_p*e(t). If MV is the absolute water valve position that means the water valve is also only opening at 15% for a water temp of 55 degrees. This doesn't make sense.
What MV is how much corrective action we apply. We have error in the system, we apply more corrective action. The effect of the corrective action is that it changes something in the system. So in the water valve example, the corrective action is turning the valve, not the absolute position of the valve itself. 122.57.201.57 ( talk) 13:36, 27 June 2010 (UTC)
The block diagram shown in the corner is of a style commonly used in control theory, and I believe it comes from diagrams describing analog computers and some electronic signal processing (or at least, the same style of diagram turns up in those places). However, the name "Block Diagram", is used by many disciplines to mean many things, it gets used in control theory to mean this specific type of diagram where the arrows represent signal flow and the blocks represent processing stages, also with the summing junctions and the Sigma symbol in the junction. I can't find a wikipedia page specifically describing the type of block diagram used by control theory, nor can I find a precise name to distinguish this type of diagram from the more generic concept. In partial answer to my own question, there's a category on commons Category:Control_theory_block_diagrams which probably should have a companion wiki page Control theory block diagram and maybe also related to Function block diagram but not exactly.
The plots in this section are essentially meaningless, since there is no explanation for how PV is related to u(t). Certainly, the generation of the plots required some relation between these terms, and without it explicitly defined, the reader is left confused. Whoever made those plots should fill in the details. —Preceding unsigned comment added by 84.108.63.99 ( talk) 05:32, 28 April 2011 (UTC)
Hello,
For the Proportional Term, I think it's wrong in the graph of "Change of response for varying Kp". The black curve with smaller oscillation should have a smaller proportional gain Kp. The red curve with bigger oscillation should have a bigger proportional gain Kp. But in the graph, it seems wrong way round. So by my understanding, the black curve should have Kp=0.5 and the red curve should have Kp=2. Am I right?
Many Thanks,
Li
The page has it correct. A higher proportional gain will increase response time. Notice how the black curve approaches the command at a faster rate then the others.
On the other hand the red curve, with the smallest gain out of the 3, has the slowest response and thus the largest overshoot.