PIC Controller The working principles of a PID controller
A proportional-integral-derivative (PID) controller is a control loop mechanism widely used in industrial control systems and other applications that require continuously modulated control.
As implied by its name, the PID controller combines proportional control with additional integral and derivative adjustments, helping the unit to automatically compensate for changes in a system.
PID controllers are widely found in a range of industrial applications and account for roughly 95 percent closed-loop operations of the industrial automation sector. They can be found in everything for position control and the regulation of temperature of mass quantities of fluid that can take days to change by a single degree.
PID controller basics
As a feedback controller, the PID controller’s core purpose is to force feedback to match a setpoint, for instance, a climate control system that forces a heating or cooling unit to turn on or off based on a set ambient temperature. It is also used to regulate other process variables such as velocity, pressure, and flow.
PID control can be said to work much in the same way as the cruise control system on a car, where external influences such as steep hills would decrease speed. In this application, a PID system would use an algorithm to restore the vehicle to its setpoint speed by controlling the power output of the vehicle’s engine as it travels up and over the hill.
Before the invention of microprocessors, PID control was achieved by analog electronic components. Today, however, all PID controllers are handled by microprocessors.
The working principles of the PID controller
The working principles of the PID controller are best understood by breaking it down and analyzing each element individually.
Proportional gain—This gives an output that is proportional to current error (the difference between what you want and what you have). If, for example, a room’s temperature setpoint is 22°C, but the room is actually at 24°C (an error of 2°C) the controller applies a corrective action that is proportional to the error—in this scenario, it may turn the heat to a medium setting, whereas it would set it to a high setting if the room’s temperature was say 15°C.
Integral gain—This is multiplied by the integral (or sum) of the error by looking at its history. Returning back to the temperature example, the system may detect that 10 minutes were spent at 24°C, 10 at 23°C, and 10 at 22°C as the room cools down. If a system is heading too slowly to a setpoint, the integral error begins to increase and makes the correction stronger, in this case, perhaps by turning the heater down to a lower level.
Derivative—This is how fast the error is changing. With the temperature example, the room is cooled by 1°C every 10 minutes. This means that the error is shrinking by 1°C, even 10 minutes. By keeping track of this, overshoot—such as making the room too cold—can be avoided, improving system efficiency.
Reasons to use PID
In short, PID is used for more precise control of the variable that is subject to control. It can also respond quickly to changes, making systems more efficient.
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