Understanding PID Control
This series provides an introduction to proportional-integral-derivative (PID) control.
PID is just one form of feedback controller, and it can be fairly easy to understand and implement. It is the simplest type of controller that uses the past, present, and future error, and it’s these primary features that you need to satisfy most control problems. That is why PID is the most prevalent form of feedback control for a wide range of real applications.
Often, when learning something new in control theory, it’s easy to get bogged down in the detailed mathematics of the problem. So in this series, we’re going to skip most of the math and instead focus on building a solid foundation.
Throughout this series, you’ll learn what a PID controller is, how to modify it to make it more robust, and you’ll get an overview of tuning methods. Along the way, you’ll understand how PID controllers are used to handle practical applications like actuator saturation and the anti-windup algorithms that protect against it, sensor noise and the derivative filter that is required, and multi-loop control.
Explore the fundamentals behind PID control. This introduction skips the detailed math and instead jumps straight to building a solid foundation. You’ll learn what a controller is used for and why PID is the most prevalent form of feedback control.
An ideal PID controller can fail when implemented on a real, nonlinear system. This video expands beyond a simple integral and outlines a few changes that protect your system against saturation, one of the most common nonlinear problems.
Expanding Beyond a Simple Derivative
Noise is generated by sensors and is present in every system. The derivative in an ideal PID controller amplifies high frequency noise. This video describes how to modify the derivative path to reduce the noise before it impacts the controller.
PID tuning depends on a system’s characteristics, which is why a one-size-fits all method doesn’t exist. Rather than presenting one method, this video is a guide for understanding the overall picture.
There are many PID tuning methods available if you have a mathematical model of the system. This video presents three different ways to model your system so that you can take advantage of each of these methods when tuning your controller.
Manual and Automatic Tuning Methods
If you have a model of a physical system, you can use it to tune a PID controller that will work to control the physical system. This video presents several PID tuning techniques that use a mathematical model.
This video covers two important concepts in PID control: cascaded loops and discrete systems. Both concepts are fundamental to most practical control systems, and they each change the way you approach and think about your problem.
