You've all probably been in a similar situation - you became aware of an underperforming PID loop, took immediate action, tuned the loop and at the end of the day the PID loop was still performing well. The next day the operator complains; the loop had been oscillating all night and is now in manual mode. The first thing you need to do is check the PID parameters and tune the loop again, the operator isn't happy, and neither are you. You could prevent this if you calculated the robustness of the controller. Learn in this blog how to consider robustness by looking at your PID parameters in your PID tuning.
PID parameters - what is the robustness of a PID controller?
If you look at your plant as a system, it will behave in a certain way in a given working point and under external conditions. If the plant moves to a different operating point or if the external condition changes, your plant might behave differently. Robustness is defined as the measure (phase margin and gain margin) of the difference in process behavior a controller can handle before the closed-loop behavior becomes unstable. Given a set of PID parameters and the model of your plant, you can calculate how much the model can change until the controller starts to oscillate. Whenever process changes arise, your PID controller manages to stay stable because you considered these robustness margins. How much margin you need is still an engineering decision. Knowing your plant, you can judge whether you need a lot of margins. When you tune for these uncertainties - or changing behavior - you can make sure your closed-loop behavior is always stable.
Why is robustness crucial in PID tuning?
The most dominant reason for robust control is safety. Unstable closed behavior is the last thing you want in a plant. Safety even overrules the controller's performance criteria such as tracking performance or the ability to deal with disturbances. Using a trial and error tuning method gives you no indication about the robustness. In other words, you have no idea how robust the controller is after tuning. Your controller may become unstable, start to oscillate or even trip your plant after some time.
A well-tuned controller always has to stabilize the process under all circumstances. If you incorporate robustness margins, the controller will remain stable, and you can warrant safety and stability. The price you need to pay for more robustness is sometimes a little less performance. Still, the difference is often marginal, and the benefits related to maintainability, ease of use, and ease of tuning are huge.
How to tune a robust PID loop?
Before you determine the P, I, and D parameters, you set the robustness margins of the controller. To estimate the margins, you need to analyze and estimate how much process uncertainty there is or how much the behavior of the process can change. It's crucial to find a perfect balance between robustness and performance. A good start is to define a gain margin of three, meaning that the process gain can go up by a factor three before the controller gets unstable. In case you set the gain margin to two, a (slightly) more performant controller will result. You want to have a perfectly tuned loop as fast as possible, but you need to make a trade-off between performance and robustness.
Is your head spinning already? These are difficult Nyquist stability criteria that are almost impossible to consider without a PID tuning software. PID Tuning software is capable of making a tradeoff between robustness and performance. All in all, using PID tuning software offers you more stability and safety and will make the life of the control engineer and process manager easier. Wonder what benefits PID tuning software like PID Tuner can offer you? Request a demo.
Or would you like to talk to a control expert right away? Ask your question here