Dear JCH! Even if You gain no applause on this group, the target You aim to is very good. And it's a dream for every control engineer to make it working. I fully disagree with You Peter, that we need transfer function to control anything.Please answer yourself a question: Does Formula 1 driver knows transfer function of anything? This proves, that control without transfer function is possible. AND THIS IS FUTURE - realtime system approximations! Question to JCH? How You estimate z1 and z2 disturbance. Is it a constant,time invariant value?
Get what working? JCH's examples ignored reality. The assumptions weren't stated, units were not used, work wasn't shown. Doesn't this bother you? Don't infinite gains bother you?
JCH has his transfer function, why do you single me out? I just am trying to show a better way than tweaking gains and drinking coffee.
It takes a long time to train, tune, a Formula 1 driver and drivers can't be duplicated. People can eventually be trained, tuned, to be very good controllers but industry doesn't have the time. If I can determine the system model in few minutes then I can save a lot of time tuning a system by trial and error. Better yet, if I can write an auto tuning program that saves my customers time and money.
Sure, but that isn't engineering that is guessing or trail and error. So must every end user learn how tune using trial and error? How much time ( money ) with this take?
Ah, Peter! Thank you for answering "user". I was waiting until I could muster the necessary patience and calm, and you saved me the effort. His message was so full of misconceptions I didn't know where to begin.
Please take into account, that nowadays we don't have controller which would compete with third rank driver.And that's because what You, Peter, have mentioned: we have 5 minutes for tuning, and it should work for decades.
5 minutes tuning is good to get money from Customer.They loop must tune itself all the time.That's what I tempt to.
In one huge factory they purchased software for loop monitoring (chemical process). And they found out, that even if they have control engineer onsite, the 80% loops are badly tuned. And installation was very fine, did fast, tuning took " 5minutes ". Your point of view come from the ground, that because nobody counts losses of mistuned loops, there are not losses.
All what I've said here could be rubbish for You, but I appreciate your time.
It depends, what target we have. If we are short time runners You are right. But if we consider long term performance You are wrong. 80% of loops I dealt with didn't have D term, because it makes problems in the future.NOT DURING INSTALLATION (your 5 minutes). Almost every of these loops performs better with D in mind. That you must've experienced as well Peter.Everybody knows it.
But we still don't know good solution for this.
Maybe we talk about the same but different languages.
Hi Peter again! I've just studied your paper (pdf) with crane's load example. Maybe I've missed it, but where is the load weight factor in your PID loop.Does this crane have fixed load?
How do you design control without transfer function? Actually you don't have to estimate anything, you cn measure them if they are observable. Now, how do you know if something is observable without put them into an observable canonical form. The question also applies to controllability, stability, sensitivity, robustness and so on.....
I can't imagine what kind of engineering work this is. Especially about robustness: will it work. Please show me if it is robust.
I never said the tuning should last forever. Machinery changes slowly as things wear. It shouldn't change like the weather. If it does then there is something that needs repair.
How do you do that without a transfer function? One could use recursive least squares. One could also make small changes in the gains and try to find the gradient. This last method would be slow but it would work without a model. We have used used that method in a more manual way.
So who's fault is that?
This phrase doesn't make sense.
that because nobody counts
Who's fault is that?
I don't see the point you are trying to make with this post.
How am I wrong? What is wrong with tuning the system? It seems you just want to argue without being specific
Why D term terms cause problems? You must be specific. What does this have to do with me?
FOPDT, first order plus dead time systems do not require a derivative gain. However, just about all of my motion systems do. First order velocity systems don't. You have a limited view of the different types of control systems.
NOT DURING INSTALLATION (your 5 minutes). Are you suggesting that just because the plant changes one should use the derivative gain? That is the wrong approach. One should try to reduce the variations in the process if the gains change that much.
Again, you must be specific. It still seem like you just want to argue.
The load isn't important as the damping factor and natural frequency don't depend on it. What I did neglect to show is the load must not be so large relative to the crane that the 'tail wags the dog'. I admit that I made an assumption that the crane and move the load without the swinging of the load affecting the crane too much. You are the first to pin me down on that. At least you are paying attention. A better simulation would take into account that it is force that moves the load, not position. I didn't say this in one of my previous post. I was just trying to make a point not make a work of art.
BTW, can you figure out how the load moves into position without swinging?
I just want to chime in on this thread for a moment. After studying Control Engineering at Univ. of Manchester, and a 30 year career with a large integrated oil refiner, i can say from solid experience that User seems to be confused about the need for a process transfer function in order to tune loops. Plant commissioning and loop tuning is a vast subject, and much has been written about it. I also wrote a book on the subject from a practical viewpoint for control engineers in the field.
In a nutshell, i see three broad categories of of tuning needs: 1) Commissioning phase of a process unit or units 2) Final tuning of recently commissioned loops 3) Ongoing monitoring and adjustments to tuning of loops as units age
For category 1) i recommend a table of conservative tuning constants to get the plants up and running. Loops include flow, pressure, temperature and so on. Category 2) requires that one obtains a process transfer functions obtained from simple plant tests. For multi-variable systems this can be quite a lot of work. After the transfer functions have been obtained and verified, one can develop tuning constants using a variety of well proven methods. I teach a graphical approach. The majority of loops do not required derivative action. Category 3) requires the same techniques for Category 2). It is a simple fact of life that loops go "out of tune" when (a) the process ages due mainly to fouling of equipment (heat exchangers), (b) throughput is permanently increased or decreased (variable gain tuning comes to mind), (c) debottle-necking which has combined effects of (a) and (b).
Trial and error tuning as used in the Ziegler-Nichols (and other) methods is usually frowned upon by the process operator on duty in the control room(s) because you will be causing the process to oscillate. Similarly, plant step tests to get the transfer function can often be difficult to do because one has to introduce a disturbance that can be distinguished clearly from the normal noise signal.
I firmly recommend that one obtain a process transfer function (First-Order-plus-Dead-Time [majority of processes], or Second-Order-plus-Dead Time [few processes]) in order to derive suitable tuning constants for the standard PID control algorithm. There are many forms of PID algorithms, and one needs to know which form is used in the DCS (sometimes PLC), or computer control system one is employing to calculate the correct tuning parameters.
From the simple experiment (key swinging on the thread) You may see that damping depends on load wieght.If the crane would cary 3 pensils, it didn't care it's speed. I don't know if your experiment is for lab purposes or industry.
I would start from observing all measurable system data, like for example motor currents. motor current change (on trolley) is related to rotational acceleration of the load.There is a full bucket of information about the system.
Yes, the damping does vary due to air resistance and the length of the cable. From other peoples research a damping factor of 0.04 is typical but it can be as high as 0.1. There are a lot of .pdf files on this.
I was just trying to show how one can control JCH's cart by a much easier method. It wasn't complete but at least it didn't assume the cart moved instantly as JCH's example did.
Yes, rotational and just the mass of the cart or trolly and the weight and angle of the load. There are .pdf files on this that show how the load affects the trolley. I took a short cut and assumed the cart would not be affected too much by the load.
If you look at the graphs you can see I plot the actual position ( cart position ) and the load position. I don't have a motor big enough but I have a hydraulic system that can move a swinging load. The problem is the hydraulic system is very powerful relative to any loads I can suspend from it so I don't think I would learn much. It may make a good video though.
I-PV is just the form of PID that I used. The integrator is in the forward path and the proportional and velocity feedback gains are in the feed bacl path. The trick is how I modified the simple target position = velocity times time motion profile. If you look at the green line you can see the control output does not look normal for following such a simple motion profile. Notice also the difference in the cart position and the load positions. The cart position is ahead of the load during the first half of the move and behind the second half of the move.
Yes, the goal is to make it so a 5 year old can move the cart and the load safely and quickly.
What about using accelerometer at the end of rope? It simplifies everything when comparing load and trolley accelerations. That way You can make the whole system more rigid to external disturbances like wind, trolley track angle change,load swing direction (these which are unpredictable) etc. I would suggest self configurable state space model, then just a PID based on transfer function estimation.
I real world implementations accelerometer can be built into the hook, supplied with battery, and comunicating via radio freq. with controller using rope as antenna(depending on wave ofcourse) .The cost would be less then 10$
I think You realize, that swinging on the real crane is a 3-dimensional process !! Modern cranes don't go step by step, but move all directions all together!!! You need 3 PID loops with decoupling. And not only cranes.
Thank you. Why trial and error? Maybe something like adaptive, linearization, or stochastic control maybe better. Trial and error? Is it a method? A method call trial and error? Does it give a final state? Final value?
I still don't understand the method call trial and error. Seems to me very confusing.
Seems to me that if transfer function is not known, then we don't know about the characteristics of the process. Anyway, it's very, very confusing. And I don't think anybody will trust trial and error method. Because it an error you make and causes unstable to the system.
Recall that An Unstable System is Useless. So my conclusion is trial and error is useless, because the system can be unstable.
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