A proportional–integral–derivative controller (PID controller or three-term controller) is a control loop mechanism employing feedback that is widely used in industrial control systems and a variety of other applications requiring continuously modulated control. A PID controller continuously calculates an error value, e(t), as the difference between a desired setpoint (SP) and a measured process variable (PV) and applies a correction based on proportional, integral, and derivative terms (denoted P, I, and D respectively), hence the name.
Topic
Proportional-Integral-Derivative (PID) Controller
This topic includes the following resources and journeys:
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Experience
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Peter Ponders PID - Why PID with 2nd Derivative Gain?
If you have ever tuned a hydraulic system and wondered why PID control didn't work better than PI control the answer is here. Since the 1980s people have kn...
See MorePeter Ponders PID - Integrated Time Absolute Error - 4 Pole example
This video shows how to calculate the coefficients for a 4 pole ITAE and how to use the 4 pole ITAE to calculate closed loop controller gains.
See MoreDirect Synthesis Method Numerator Dynamics Problem
I walk through how to design a PID feedback controller when given a second order process with numerator dynamics, using the Direct Synthesis Method.
See MorePeter Ponders PID-Fuzzy Logic vs PID
There are many academic and engineering papers showing how good fuzzy logic control is relative to PID control. Every FL vs PID paper I have seen compares...
See MorePID Control - A brief introduction
In this video, I introduce the topic of PID control. This is a short introduction design to prepare you for the next few lectures where I will go through several examples of PID control....
See MorePeter Ponders PID - T0P1 Part 4, Misc Topics
This video covers another way to compute symbolic gains, the difference between having the P gain act on the error or just the feedback, extending bandwidt...
See MoreUnderstanding PID Control, Part 3: Expanding Beyond a Simple Derivative
This video describes how to make an ideal PID controller more robust when controlling real systems that don’t behave like ideal linear models. Noise is generated by sensors and is present in...
See MoreCascade Control Intro
How can we improve the disturbance rejection of our controllers using additional, relevant measurements? Tune in to find out!
See MorePeter Ponders PID, Natural Frequency vs Frequency of Acceleration
This video is intended for servo hydraulic system designers and those that program hydraulic servo systems but it does show how several of the techniques sho...
See MoreControl Bootcamp: Cruise Control Example with Proportional-Integral (PI) co...
In this video, we show that introducing integral control reduces the steady-state tracking error to zero in the cruise control example. We also use a more sophisticated model for the...
See MoreDesigning a PID Controller Using the Ziegler-Nichols Method
In this video we discuss how to use the Ziegler-Nichols method to choose PID controller gains. In addition to discussing the method and providing a Matlab i...
See MorePeter Ponders PID - Cascade Control Part1
I cover whether cascade control is necessary. Why there needs to be a feed back for every loop. How to calculate gains. Bode plots and ratio of the inner t...
See MoreUnderstanding PID Control, Part 2: Expanding Beyond a Simple Integral
The first video in this series described a PID controller, and it showed how each of the three branches help control your system.That seemed simple enough and appeared to work. However, in...
See MoreAuto Tuning a Small DC Motor in Torque Mode
I was really testing the picture in picture feature of the Screen Flow software I use to make these videos. I knew the auto tuning would work. I kept the v...
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