PID

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PID

PID

(1) (Process IDentifier) A temporary number assigned by the operating system to a process or service.

(2) (Proportional-Integral-Derivative) The most common control methodology in process control. It is a continuous feedback loop that keeps the process flowing normally by taking corrective action whenever there is any deviation from the desired value ("setpoint") of the process variable (rate of flow, temperature, voltage, etc.). An "error" occurs when an operator manually changes the setpoint or when an event (valve opened, closed, etc.) or a disturbance changes the load, thus causing a change in the process variable.

The PID controller receives signals from sensors and computes corrective action to the actuators from a computation based on the error (proportional), the sum of all previous errors (integral) and the rate of change of the error (derivative). See PAC.


Inputs from a PID
The large white boxes are Opto 22 SNAP PACs, which are programmable automation controllers that are processing the PID loops in Chevron's research facility in Richmond, Virginia. The wires come from thermocouples that sense pipe temperature in a laboratory test that analyzes the best way to break down crude oil. The PACs determine when to raise and lower the temperature, and the three modules with the black sockets send digital signals to the heaters (cables not connected in this image). (Image courtesy of Opto 22, www.opto22.com)
References in periodicals archive ?
So far, a comprehensive method has been presented to compute the entire set of stabilizing PID controller parameters for a FOPDT model.
Please note that this derivative action (RTL) is separate from derivative action of a normal PID controller as this D-action is only concerned with opening of control valve whereas in a PID controller, derivative action takes part in both opening and closing of the valve.
5c (Control performance of PID based on Genetic Algorithm) demonstrates the control characteristics of air conditioning system after the optimization of PID controller performed by classical genetic algorithm operation.
Workshops focus on proven best-practices for assessing and optimizing a production facility's PID controllers.
For a typical PID controller, the controller output signal u(t) can be written as the following in time and s domain [18]:
The vehicle dynamics responses with the assistance of the proposed FO-PID controller are compared against those with traditional PID controller and with no control at all, respectively, which is shown in Figure 9.
In the above math model switching device is controlled by the PID controller which gets the error signal from the feedback path consist of comparator.
Therefore, the fuzzy PID controller can be designed according to the following two processes.
With simple structure and good performance, the classical controller such as PID controller relies only on the measured process variable, not on knowledge of the plant mathematics model, making it a broadly useful controller.
A lot of practice showed that every PID controller parameter (proportional gain, integral gain, and derivative gain) has its own effectiveness to control system clearly, which is very easy to operate and also very effective.
In [8], a hybrid Firefly Algorithm optimized fuzzy PID controller for Load Frequency Control.