(Control) Derivative filter and discrete model

Thread starter Leo Liu
Start date Nov 15, 2023
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Modeling Simulink

AI Thread Summary

Adding a derivative filter to a discrete system in Simulink significantly improves performance by reducing settling time and is often necessary for optimal control. The discussion highlights the effectiveness of a discrete PID controller combined with a second-order discrete transfer function. The user seeks clarification on the underlying reasons for this behavior and questions whether to model a physical system like F=ma as discrete or continuous. Insights on these modeling choices and their implications for system performance are requested. Understanding the advantages of derivative filtering in discrete systems can enhance control strategies in various applications.

Nov 15, 2023

Leo Liu

Hi I am back :).

I have been doing some Simulink modeling for a project. I modeled it with a discrete system due to the controller rate. I have noticed that for all the discrete system I have tried, adding a derivative filter not only improves the performance (smaller settling time), but it is sometimes also necessary.

The following example involving a discrete PID and a 2nd order discrete transfer function illustrates the behaviour:

Autotune with no derivative filter N:

Autotune with derivative filter N:

I was wondering why such a behaviour would occur. Also, should I model the transfer function as discrete or continuous system for a physical system like F=ma? Any input will be appreciated.

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