By the end of this section, you should be able to understand

1. The general concept of feedback control

2. How using amplification of error as input into a system can change its behavior (P Controller)

3. How using amplification of the sum of the error as input into a system can change its behavior (I Controller)

4. The success of a controller is dependent on the “plant” and the desired response

This section introduces feedback control, the central idea behind closed-loop systems that automatically correct their behavior by comparing what you want to what you get. You will learn how the error signal drives the controller, how that control input changes the plant response, and why feedback can improve tracking and reduce sensitivity to disturbances when it is designed well. The lessons start with motivation and the basic feedback architecture, then move into proportional control, where a P controller amplifies error to shape speed of response, overshoot, and steady behavior. Next, you will study integral control, where an I controller amplifies the accumulated error to eliminate steady-state error, while also creating new tradeoffs that you must recognize in real systems. A recurring theme in this section is that controller success depends on both the plant dynamics and the response you are trying to achieve, so you will focus on interpretation as much as computation. Use the table of contents below to jump between the introduction, the proportional control example, the integral control example, and the lecture code so you can practice the workflow of defining a desired response, modeling the plant, forming the error, and evaluating how feedback changes system behavior.