PID | Notion

https://colab.research.google.com/drive/1iH441nBdNAImWpENkxJD3O9LEGpihRxz?usp=sharing&utm_source=youtube&utm_medium=description

PID, or Proportional-Integral-Derivative, is a type of control system widely used in various industrial applications. This control system is instrumental in managing processes by calculating an "error" value, which represents the difference between a measured process variable and a desired setpoint. The goal of the PID controller is to minimize this error by adjusting the process control inputs accordingly.

There are three crucial components to a PID control system: the Proportional term, the Integral term, and the Derivative term.

The Proportional term is the first and simplest component. This term produces an output value that is proportional to the current error value. This means that if the error is large, the control output will also be large, and vice versa. This component helps in reducing the overall error, making the system more stable and less prone to oscillation. However, it cannot completely eliminate the error, which is where the next two components come into play.
The Integral term is the next component. This term is proportional to both the magnitude of the error and the duration of the error. This means that the longer the error persists, the larger the integral term becomes. The main purpose of this term is to eliminate the residual error that the proportional component cannot remove. It does this by adding a control effect due to the historic cumulative value of the error. Once the error is entirely eliminated, the integral term will cease to grow, preventing the system from becoming unstable.
The Derivative term is the final component. This term is proportional to the rate of change of the error. This means that if the error is changing rapidly, the derivative term will be large, and vice versa. The primary purpose of this term is to dampen the system, reducing the effect of sudden changes in error by predicting the future behavior of the error. This prediction can help prevent overshooting and undershooting, improving the overall stability and responsiveness of the system.

One of the main reasons for the widespread use of PID control systems in various industrial control systems is their robust performance across a wide range of operating conditions. In addition, their simplicity of use makes them a desirable choice for many applications, from temperature control in ovens to speed control in vehicles.

In addition to the aforementioned applications, PID control systems also play a crucial role in the automation industry. They control automatic systems in factories and plants, adjusting the inputs to ensure the output remains at the desired level, despite any disturbances or changes in conditions. For example, in an automated assembly line, a PID controller can adjust the speed of the conveyor belt based on the number of items being processed, ensuring a constant production rate.

PID controllers are also fundamental to the functioning of drones and unmanned aerial vehicles (UAVs). They help maintain the balance and stability of these devices while in flight. For example, they adjust the speed of the motors based on the drone's tilt angle and rotational speed to keep it stable.

In the field of robotics, PID controllers are used to control the movement and actions of robots. They can be used to control the speed and direction of a robot's movement, the movement of its limbs, and even the operation of its sensors and other equipment.

In the field of energy management, PID controllers are used to regulate the output of power plants, ensuring a constant supply of electricity. They can also be used in the management of renewable energy sources, such as wind turbines and solar panels, to maximize their efficiency.

Overall, the PID control system's ability to accurately control a system's output by minimizing the error, along with its simplicity and versatility, has made it an indispensable tool in various industrial applications. It's expected that with advancements in technology, the use of PID controllers will only increase, particularly in fields such as artificial intelligence and machine learning, where precision control is crucial.

Watch this video and some notes regarding this

https://www.youtube.com/playlist?list=PLn8PRpmsu08pQBgjxYFXSsODEF3Jqmm-y

PID-Matlab

PID is just like integration if u see closely see this cmu video and get hands on pid

https://www.youtube.com/watch?v=dR0nTvZqabQ

aslo get in touch with these profs

https://docs.google.com/presentation/d/1CHVR7nh-2-SdZxt-xocDPLvagkQpQel5sC74CIVBgtI/edit