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    Metal PID Controller

    • MaterialMetal
    • ApplicationIndustrial
    • DurabilityLong Life
    • ResistivityRust Resistant
    • Supply TypeManufacturer, Exporter, Supplier, Retailer
    • Preferred Buyer Location All over the world
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    • calendar Member Since 14 Years
    • building Nature of Business Retailer
    • gst icon GST No. 27ALCPG7812M1ZX

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    • MaterialMetal
    • ApplicationIndustrial
    • ResistivityRust Resistant
    • Surface FinishingPolished
    • Drive TypeElectric
    • DurabilityLong Life

    A proportional-integral-derivative controller (PID controller) is a generic control loop feedback mechanism (controller) widely used in industrial control systems. A PID controller calculates an "error" value as the difference between a measured process variable and a desired setpoint. The controller attempts to minimize the error by adjusting the process control inputs.
    The PID controller calculation algorithm involves three separate constant parameters, and is accordingly sometimes called three-term control: the proportional, the integral and derivative values, denoted P, I, and D. Simply put, these values can be interpreted in terms of time: P depends on the present error, I on the accumulation of past errors, and D is a prediction of future errors, based on current rate of change. The weighted sum of these three actions is used to adjust the process via a control element such as the position of a control valve, a damper, or the power supplied to a heating element.
    In the absence of knowledge of the underlying process, a PID controller has historically been considered to be the best controller. By tuning the three parameters in the PID controller algorithm, the controller can provide control action designed for specific process requirements. The response of the controller can be described in terms of the responsiveness of the controller to an error, the degree to which the controller overshoots the setpoint, and the degree of system oscillation. Note that the use of the PID algorithm for control does not guarantee optimal control of the system or system stability.


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