Industrial Fuzzy controller

Dear All, Do anyone has worked with a Fuzzy controller in an industrial plant (a true world ). I need to know about the actual response of these controllers.
Is it better than the traditional PI or PID controllers.
Thanks to you all.
Regards,
Hesham Elhadad
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It really isn't a case of "better" or "worse" response. In many cases, normal PID controllers are perfectly adequate. These include the "single input - single output" controls.
The fuzzy set controls I worked with dealt with multiple input, multiple output systems. In these cases, it isn't unusual to have actions which are based not only on the magnitude of deviation from setpoint, but the direction of deviation (in several dimensions). PID, without a bit of work, will have one action for a high process value (eg, open cooling water valve), and its opposite for a low process value (close cooling water valve). Fuzzy sets can have one strategy for high values (open cooling water valve, reduce reactant feed rate) and another for a low process value (add reactant), and another for a very low process value (add steam, turn off reactant).
Have I obfuscated the difference enough?
Michael

true world ).

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snipped-for-privacy@soficom.com.eg (Hesham Elhadad) wrote in message

Siemens have for their S7 series of PLCs fuzzy and neurofuzzy control. For 95% of applications PIDs are perfect and for the remaining 5% about 3% are adaquete.
Fuzzy is excellent for capturing linguistic knowledge such as "if getting to medium hot very fast then reduce heat input to lower and turn fan on low" this info may not be an the form of a known model or equation.
Neurofuzzy helps you tune those rules without actualy getting and expereienced plant opperators knowledge into human language: you just let the neruofuzzy learn as it observes the actions.
From my understanding fuzzy is usefull in improving and optimising plant which is poorly understood becuase it is non linear and multiple inputs and outputs and hasn't been or can't succesfully be modelled or measured. It is a way of capturing human knowledge and implementing it into control.
Siemens have some example projects: I think concrete plants are one.
In some cases a system that requires two PID loops and thus two sensors eg voltage and current in some variable speed drives these can be reduced to only one fuzzy loop with only one voltage sensor thus saving some cost and not loosing performance.
They've been used to estimate whether a car driver is trying to save fuel, trying to drive fast or trying to drive on slippery snow and then adjust accordingly. I think VW Golfs have had these for years.
Don't use it as a substitute for lack of knowledge of PIDs.
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And don't forget that when you start using a fuzzy controller you're launching yourself squarely into the world of non-linear control -- you you gonna guarantee stability?
<snip>

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Actually, I've found fuzzy controllers to be quite stable, often more so than PID controllers. This is probably because they are able to handle coordinated responses of many variables while PID cannot.
Michael

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Thanks for all of you Guys
I think the picture becomes more clear for my eyes now. It is clear that the PID still has the power as a perfect controller over the new technologies which is still under research. Actually, I have studied the fuzzy logic for two years but I have not supervised it working in nature. In my working field (DCS) almost of the control is based on the traditional (PI) control algorithm only. I have never worked on the siemens PLC before, and hope to do one day.
Thanks for you again,
Look forward to hearing from you soon.
Regards,
Hesham Elhadad
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PID control is best for siso systems which are well defined with a single control rule or a cascaded set of rules. Fuzzy controls are best for mimo systems which are poorly defined (or understood), have multiple control rules, show some nonlinearity, or require disparate actions in different areas of the operating plane. Generally, I've seen fuzzy sets being used in supervisory control systems, with PID controllers running the individual regulatory loops. That combination allows both systems to be used to their greatest advantage.
As far as perfect control, I'm not so sure. I've dealt with a lot of systems which work fine on PID. I've dealt with a few which did ok on PID, but much better on a fuzzy controller. I've seen a couple in which fuzzy sets didn't work (PID wouldn't either). In those cases, there was an underlying engineering problem with the unit operation.
Each type of control has its place. DCS systems tend to only have the PID algorithms on them because they are well known, and expected. They are also derivatives of the old pneumatic controls. Fuzzy sets came much later, and DCS vendors don't seem to be too quick to put new methods in. If they put in fuzzy sets, they would have to put in DMC, eDMC, neural networks, lambda tuning, process bots, etc, and they don't want to go through the effort. It is quite frustrating to see a system which would benefit from a higher level of control, only to be stopped by a controller which hasn't been programmed to deliver that control method.
Michael
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