Hi all,

I have an first order plus time delay system with K=58.46, T(time constant)=0.55s, Td(Time delay)=0.06s and i had some trouble in design this PI Controller by using Ziegler Nichols tuning method.

The system is defined as G=58.46/(0.55*s+1)*exp(-0.06*s)

There is some calculation given by ZN tuning method for FOPDT system
where Kc=0.9*T/(K*Td) and Ti=3.33*Td

I had work out for the Kc and Ti and found that

Kc=0.9*0.55/(58.46*0.06)=0.1411

Ti=3.33*(0.06)=0.2

Gc is given that Kc*[1+(1/Ti*s)],
so Gc=0.1411*[1+(1/0.2s)] = 0.1441*[(0.2s+1)/0.2s]

but once i put this Gc into my system by Simulink, my wave seen oscillated very much. Can anyone tell me what i had done wrong and which parameter should i tunning ? Can i tune the Kc from 0.1411 to another value like 0.7?
Thankyou very much.

 

Perhaps you should have stayed within your original thread as this will only lead to confusion.

In any event it looks like your simulation time step is too coarse. Try making your time step an order of magnitude smaller.

I did a simulation using another application using your values and the response looked fine. My time step was 1msec.

I notice however your PI proportional gain in the block diagram is 0.1441 whereas you have Kc as 0.1411 in the post body text.

 

When I say the response looked "fine" I should qualify that description and say that the response was probably overly oscillatory. See my attachment.

Given the overshoot is of the order of 70% I would suggest a reduction in the PI gain would possibly improve matters.

 

However reducing the gain too much will lead to other problems as the phase margin of the combined PI controller and System decreases.

 

Also keep in mind the Ziegler-Nichols method is based on an experimental approach in which one disables the 'I' control in the closed loop and then increases the P gain until the loop goes into quasi-steady-state oscillation.

The observed proportional gain at oscillation onset and the measured period of self oscillation are then used to propose a stable set of PI settings.

I'm not sure how well Ziegler-Nichols predicts the PI parameters for systems with transport delay.

I played around the the P gain and got the loop oscillating at a P gain of ~0.25. The oscillation period was 0.23 sec. Wikipedia suggests the gain should be backed off to 0.25/2.2=0.114. The I gain would be set to 2*0.114/0.22=1.04. Interestingly this produces an even more oscillatory response [~80% overshoot] when I plug the values into my simulation. This then makes me wonder whether Ziegler-Nichols is actually the correct approach.

As a matter of interest I am using a 3/4th order Pade approximation of the 0.06sec transport delay - my simulation application doesn't have a means of emulating a continuous pure delay when working in the 's' domain.

 

Perhaps you should have stayed within your original thread as this will only lead to confusion.

In any event it looks like your simulation time step is too coarse. Try making your time step an order of magnitude smaller.

I did a simulation using another application using your values and the response looked fine. My time step was 1msec.

I notice however your PI proportional gain in the block diagram is 0.1441 whereas you have Kc as 0.1411 in the post body text.

Thank you very much,thats my fault on block diagram, it suppose 0.1411.

 

When I say the response looked "fine" I should qualify that description and say that the response was probably overly oscillatory. See my attachment.

Given the overshoot is of the order of 70% I would suggest a reduction in the PI gain would possibly improve matters.

What is the "Sample Time" on the red circle stands for? it was -1 and when i change it to 0.02, it show another oscillation which is more smooth but still 70% overshoot.



That is a different between them, how should i select my Sample Time?

 

What is the "Sample Time" on the red circle stands for? it was -1 and when i change it to 0.02, it show another oscillation which is more smooth but still 70% overshoot.

The sample time is critically important to get the right answer. The -1 means the sample time is inherited, which just means it will match the sample time of other blocks it is attached to. This is the usual setting. When you set a particular number, like 0.02, you are forcing a discrete time sample time. Since you seem to be modeling a continuous time system, I would think you don't want 0.02, but -1.

Somewhere else, in one of the other blocks, there should be a 0 for the sample time, which results in continuous time modeling. In this case the timestep parameter in the simulation configuration menu will set the sample time. You'll want to make sure that you are using a good numerical method (like Runga Kutta, ODE4) and a sufficiently small sample time (much smaller than the system dynamics and time constants). The coarse plotting is likely a result of the time step being too large. Or, it's possible that the decimation setting on the scope is too high (use decimation of 1).

If you attach your Simulink file, I'm willing to check these things for you to help you figure out the problem.

I think t_n_k is on the right track here. As he says, he is using a Pade approximation because of the limitations of Matlab linear system tools. Simulink has more capability to model delay, and it would be interesting to use Simulink to compare the real transport delay with the Pade approximation.

The Ziegler-Nichols is one approach to use, but you probably would want to tweak the final values. The thing is, you haven't established any other constraints on overshoot and risetime, and you are not looking at the open loop gain and phase margin to make judgements. Obviously stability is an implied constraint, but you have stability. So, one could argue that your solution is acceptable since you used a method and got a result that is nearly an acceptable solution. With further constraints on margins, or on overshoot/risetime, you would tweak the gains further, and have less overshoot and less ringing.

 

The sample time is critically important to get the right answer. The -1 means the sample time is inherited, which just means it will match the sample time of other blocks it is attached to. This is the usual setting. When you set a particular number, like 0.02, you are forcing a discrete time sample time. Since you seem to be modeling a continuous time system, I would think you don't want 0.02, but -1.

Somewhere else, in one of the other blocks, there should be a 0 for the sample time, which results in continuous time modeling. In this case the timestep parameter in the simulation configuration menu will set the sample time. You'll want to make sure that you are using a good numerical method (like Runga Kutta, ODE4) and a sufficiently small sample time (much smaller than the system dynamics and time constants). The course plotting is likely a result of the time step being too large. Or, it's possible that the decimation setting on the scope is too high (use decimation of 1).

If you attach your Simulink file, I'm willing to check these things for you to help you figure out the problem.

I think t_n_k is on the right track here. As he says, he is using a Pade approximation because of the limitations of Matlab linear system tools. Simulink has more capability to model delay, and it would be interesting to use Simulink to compare the real transport delay with the Pade approximation.

The Ziegler-Nichols is one approach to use, but you probably would want to tweak the final values. The thing is, you haven't established any other constraints on overshoot and risetime, and you are not looking at the open loop gain and phase margin to make judgements. Obviously stability is an implied constraint, but you have stability. So, one could argue that your solution is acceptable since you used a method and got a result that is nearly an acceptable solution. With further constraints on margins, or on overshoot/risetime, you would tweak the gains further, and have less overshoot and less ringing.

Thanks for your reply. I had upload my file here.
File name: zabpidtesting2.mdl File size: 26.86 KB

The constraints on overshoot is about 20%. If i wish to get a overshoot of 20% can i just tune to the gain to 0.025 as the picture shown below which get the result of overshoot ~20% ?

 

Your file looks pretty good. You are using a variable step solver with tolerance of 1e-3. I recommend setting the tolerance to 1e-6, for better accuracy.

You may want to consider changing the PI zero location as well as the gain. You can use a higher gain if the zero is moved to lower frequency. But, you are basically on the right track.

 

Your file looks pretty good. You are using a variable step solver with tolerance of 1e-3. I recommend setting the tolerance to 1e-6, for better accuracy.

You may want to consider changing the PI zero location as well as the gain. You can use a higher gain if the zero is moved to lower frequency. But, you are basically on the right track.

Ok, thank you very much.
Do you mean from the picture below, i m doing right track? Can i just tune the gain from 0.1411 to 0.025? In ziegler nichols rules, is that possible to change the zero to lower frequency?

 

Do you mean from the picture below, i m doing right track? Can i just tune the gain from 0.1411 to 0.025? In ziegler nichols rules, is that possible to change the zero to lower frequency?

Yes, you are on the right track. Lowering the gain would seem advisable. However, lowering the zero frequency might also help improve the response time while still meeting the overshoot requirement. For example, I've attached a block diagram and plot using a gain of 0.1 and a zero frequency of 5 rad/s.

 

I thought it would be interesting to show the effect of approximating the pure delay with a Pade approximation.

I've attached a block diagram for the simulation and plot of the step and phase response of the Pade approximation.

Then I show two plots that compare the system response with pure delay and the Pade approximation. The overall response is very accurate and the difference can only be seen in the plot that magnifies the beginning of the response.

Overall the approximation is quite good and useful and does not impact predictions of stability, ringing, overshoot, rise time etc.

 

Thanks Steve,

Very interesting what you have done. Your other insights in this thread much appreciated.

I've found the attached document also a good summary of the Pade approximation as it makes particular reference the 's' domain approximation of pure transport delay.

 

Yes, you are on the right track. Lowering the gain would seem advisable. However, lowering the zero frequency might also help improve the response time while still meeting the overshoot requirement. For example, I've attached a block diagram and plot using a gain of 0.1 and a zero frequency of 5 rad/s.

Thank you again steveb

In Ziegler Nichols rules, it said that we can tune the gain, but is that possible we can tune the zero frequency or did Ziegler Nichols said that we can tune the zero frequency? Because i need to write a report of this, so i have to follow the rules of Ziegler Nichols.
Thank you very much in helping me searching for the answer. Appreciate it very much.

 

The following link might be of interest regarding your report on Ziegler-Nichols approach ....

http://www.mstarlabs.com/control/znrule.html

 

My understanding at this point of time is that Ziegler-Nichols settings were initially proposed to produce a good response for a first order system with dead time - supposedly something commonly encountered in practical industrial control situations. So I've learned something useful.

In essence the Ziegler-Nichols method simply leads to settings for the PI or PID parameters using an experimentally based approach - with observations made on the actual plant + control system in question.

Ultimately one normally has complete freedom as to the setting of both the proportional gain and the integral gain / zero frequency etc. Whether the chosen settings are optimal is another matter. Hence the requirement for a final tweaking is not unexpected.

As an additional observation it might be worth considering what benefit there may be in adding the D control element to the mix - to make it PID rather than just PI control.

 

The following link might be of interest regarding your report on Ziegler-Nichols approach ....

http://www.mstarlabs.com/control/znrule.html

Thankyou very much T_N_K.
This might help me in writing report.

 

My understanding at this point of time is that Ziegler-Nichols settings were initially proposed to produce a good response for a first order system with dead time - supposedly something commonly encountered in practical industrial control situations. So I've learned something useful.

In essence the Ziegler-Nichols method simply leads to settings for the PI or PID parameters using an experimentally based approach - with observations made on the actual plant + control system in question.

Ultimately one normally has complete freedom as to the setting of both the proportional gain and the integral gain / zero frequency etc. Whether the chosen settings are optimal is another matter. Hence the requirement for a final tweaking is not unexpected.

As an additional observation it might be worth considering what benefit there may be in adding the D control element to the mix - to make it PID rather than just PI control.

Again, thankyou for your reply t_n_k
You means that we can tune everything freedomly? Actually from my calculation and block diagram, do i did anything wrong that cause me had 70% overshoot by using Z-N method?

 

Actually from my calculation and block diagram, do i did anything wrong that cause me had 70% overshoot by using Z-N method?

No - not as far as I can see.

If the plant is of the form

\(G(s)=\frac{Ke^{-Ls}}{1+Ts}\)

Then, based on the literature on PI control one would apparently set

\(K_p=\frac{0.9}{a}\)

and

\(T_i=3L\)

Where

\(a=\frac{KL}{T}\)

and the PI control block is defined by

\(PI(s)=K_p(1+\frac{1}{T_i s})\)

For your plant values this would give Kp=0.14 and Ti=0.18

And these settings certainly give ~70% overshoot.

I hate to labor the point but the Ziegler-Nichols approach evolved out of a 'trial-and-error' methodology developed in the early 1940's. It's not my intention to devalue the contribution of Ziegler in any way, but it's surprising we still place so much emphasis on the method given the advances in our understanding since then.

Clearly in this situation the Z-N method gives an overly oscillatory response. Perhaps one should go back to the original 1940's publication and review the exact reasons as to why Z-N chose this methodology.