(Control) Derivative filter and discrete model

Thread starter Leo Liu
Start date Nov 15, 2023
Tags

Modeling Simulink

Click For Summary

SUMMARY

The discussion focuses on the implementation of a derivative filter in discrete systems using Simulink for modeling. Users observed that incorporating a derivative filter significantly enhances performance by reducing settling time in discrete PID controllers and second-order discrete transfer functions. The necessity of the derivative filter in specific scenarios was highlighted, prompting inquiries about the appropriate modeling of physical systems, such as F=ma, as either discrete or continuous.

PREREQUISITES

Simulink for modeling control systems
Understanding of discrete PID controllers
Knowledge of transfer functions in control theory
Familiarity with system dynamics, particularly F=ma

NEXT STEPS

Explore the effects of derivative filters on discrete PID control performance
Research modeling techniques for continuous vs. discrete systems in Simulink
Learn about tuning parameters for discrete transfer functions
Investigate the impact of sampling rates on system behavior in control systems

USEFUL FOR

Control engineers, Simulink users, and anyone involved in optimizing discrete control systems will benefit from this discussion.

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.