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What is PID control?The PID controller or Proportional-Integral-Derivative control calculates an error signal, which is the difference between the set point and the actual process output, and then adjusts the input to the process based on that error signal. The Proportional term adjusts the input in proportion to the error, the Integral term adjusts the input based on the accumulated error over time, and the Derivative term adjusts the input based on the rate of change of the error signal. Advantages and limitations of PID controlPID control is a popular control method because of its simplicity and reliability. It is easy to implement and can be used for many processes. It is also a robust control method that can handle disturbances and changes in the process.However, there are some limitations to PID control. It requires tuning the control parameters for each specific process, which can be time-consuming and challenging. PID control also assumes a linear relationship between the process input and output, which may not always be accurate. Additionally, PID control does not adapt to changes in the process over time.The evolution of PID controlPID control has been around for over a century, and over the years, it has become more sophisticated. Elmer Sperry invented the first PID controller in 1911 to control the steering of ships. Since then, PID control has been used in various applications, from heating and cooling systems to robotics and automation.In recent years, there have been advancements in PID control, such as fuzzy logic and neural networks. These methods can improve the performance of PID control by adapting to changes in the process and reducing the need for manual tuning.AI and machine learning in PID control

PID control is widely used to control industrial processes. It is a feedback control system that uses sensors to measure the output of a process and adjusts the input to keep the process at a desired set point. In this blog, we will discuss in detail whether AI will replace PID control.

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