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Difference between revisions of "PID Controllers"
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'''Proportional Integral Derivative Controller (PID controller)''' is a generic control loop feedback mechanism widely used in industrial control systems – a PID is the most commonly used feedback [[Controllers]]. 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. | '''Proportional Integral Derivative Controller (PID controller)''' is a generic control loop feedback mechanism widely used in industrial control systems – a PID is the most commonly used feedback [[Controllers]]. 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 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. Heuristically, 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, or the power supplied to a heating element. | ||
The PID controller calculation 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. Heuristically, 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, 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. | 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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==Limitations of PID control== | ==Limitations of PID control== | ||
While PID controllers are applicable to many control problems, and often perform satisfactorily without any improvements or even tuning, they can perform poorly in some applications, and do not in general provide optimal control. The fundamental difficulty with PID control is that it is a feedback system, with constant parameters, and no direct knowledge of the process, and thus overall performance is reactive and a compromise – while PID control is the best controller with no model of the process,better performance can be obtained by incorporating a model of the process. | While PID controllers are applicable to many control problems, and often perform satisfactorily without any improvements or even tuning, they can perform poorly in some applications, and do not in general provide optimal control. The fundamental difficulty with PID control is that it is a feedback system, with constant parameters, and no direct knowledge of the process, and thus overall performance is reactive and a compromise – while PID control is the best controller with no model of the process,better performance can be obtained by incorporating a model of the process. | ||
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A problem with the derivative term is that small amounts of measurement or process noise can cause large amounts of change in the output. It is often helpful to filter the measurements with alow-pass filter in order to remove higher-frequency noise components. However, low-pass filtering and derivative control can cancel each other out, so reducing noise by instrumentation is a much better choice. Alternatively, a nonlinear median filter may be used, which improves the filtering efficiency and practical performance.In some case, the differential band can be turned off in many systems with little loss of control. This is equivalent to using the PID controller as a PI controller. | A problem with the derivative term is that small amounts of measurement or process noise can cause large amounts of change in the output. It is often helpful to filter the measurements with alow-pass filter in order to remove higher-frequency noise components. However, low-pass filtering and derivative control can cancel each other out, so reducing noise by instrumentation is a much better choice. Alternatively, a nonlinear median filter may be used, which improves the filtering efficiency and practical performance.In some case, the differential band can be turned off in many systems with little loss of control. This is equivalent to using the PID controller as a PI controller. | ||
==Sources== | |||
http://en.wikipedia.org/wiki/PID_controller | [http://en.wikipedia.org/wiki/PID_controller Wikipedia PID Controller] | ||