Proportional Offset Error
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mechanical examples are the toilet bowl float proportioning valve and the fly-ball governor. The proportional control system is more complex than an on-off control system like a bi-metallic domestic thermostat, but simpler
Proportional Control Offset
than a proportional-integral-derivative (PID) control system used in something like an automobile cruise proportional controller example control. On-off control will work where the overall system has a relatively long response time, but can result in
Proportional Controller Steady State Error
instability if the system being controlled has a rapid response time. Proportional control overcomes this by modulating the output to the controlling device, such as a continuously variable valve. An analogy to on-off proportional offset definition control is driving a car by applying either full power or no power and varying the duty cycle, to control speed. The power would be on until the target speed is reached, and then the power would be removed, so the car reduces speed. When the speed falls below the target, with a certain hysteresis, full power would again be applied. It can be seen that proportional integral controller this looks like pulse-width modulation, but would obviously result in poor control and large variations in speed. The more powerful the engine; the greater the instability, the heavier the car; the greater the stability. Stability may be expressed as correlating to the power-to-weight ratio of the vehicle. Proportional control is how most drivers control the speed of a car. If the car is at target speed and the speed increases slightly, the power is reduced slightly, or in proportion to the error (the actual versus target speed), so that the car reduces speed gradually and reaches the target point with very little, if any, "overshoot", so the result is much smoother control than on-off control. Further refinements like PID control would help compensate for additional variables like hills, where the amount of power needed for a given speed change would vary. This would be accounted for by the integral function of the PID control. Contents 1 Proportional Control Theory 2 Offset Error 3 Proportional Band 4 See also 5 External links Proportional Control Theory[edit] In the proportional control algorithm, the controller output is proportional to the error signal, which is the difference between the s
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Offset In Process Control
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Integral Action In A Proportional Integral Controller
October 2011 (1) September 2011 (1) August 2011 (2) July 2011 (1) June 2011 (1) May 2011 (1) April 2011 (2) March 2011 (2) February 2011 (1) January 2011 (2) December 2010 https://en.wikipedia.org/wiki/Proportional_control (1) November 2010 (1) October 2010 (2) September 2010 (1) August 2010 (1) July 2010 (1) May 2010 (2) April 2010 (1) March 2010 (3) February 2010 (3) January 2010 (2) Search After search, use << and >> links at top of page to view other pages. Get Updates on Facebook About OptiControls The Author Contact Me « Tuning Tips - How to http://blog.opticontrols.com/archives/344 Improve Your Results Cohen-Coon Tuning Rules » PID Controllers Explained March 7, 2011 PID controllers are named after the Proportional, Integral and Derivative control modes they have. They are used in most automatic process control applications in industry. PID controllers can be used to regulate flow, temperature, pressure, level, and many other industrial process variables. This blog reviews the design of PID controllers and explains the P, I and D control modes used in them. Manual Control Without automatic controllers, all regulation tasks will have to be done manually. For example: To keep constant the temperature of water discharged from an industrial gas-fired heater, an operator will have to watch a temperature gauge and adjust a fuel gas valve accordingly (Figure 1). If the water temperature becomes too high for some reason, the operator has to close the gas valve a bit – just enough to bring the temperature back to the desired value. If the water becomes too cold, he has to open the gas valve. Figure 1. An operator doing manual control. Feedback Control The control task done by the operator is called feedback co
Control controlguru Like the P-Only controller, the Proportional-Integral (PI) algorithm computes and transmits a controller output (CO) signal every sample time, T, to the final control element (e.g., valve, variable speed pump). The computed CO from the PI algorithm is influenced by the controller tuning parameters and http://controlguru.com/integral-action-and-pi-control/ the controller error, e(t). PI controllers have two tuning parameters to adjust. While this makes them http://www.online-courses.vissim.us/Strathclyde/proportional_action_analysed.htm more challenging to tune than a P-Only controller, they are not as complex as the three parameter PID controller. Integral action enables PI controllers to eliminate offset, a major weakness of a P-only controller. Thus, PI controllers provide a balance of complexity and capability that makes them by far the most widely used algorithm in process control applications. The PI Algorithm While different vendors cast proportional control what is essentially the same algorithm in different forms, here we explore what is variously described as the dependent, ideal, continuous, position form: Where: CO = controller output signal (the wire out) CObias = controller bias or null value; set by bumpless transfer as explained below e(t) = current controller error, defined as SP – PV SP = set point PV = measured process variable (the wire in) Kc = controller gain, a tuning parameter Ti = reset time, a proportional integral controller tuning parameter The first two terms to the right of the equal sign are identical to the P-Only controller referenced at the top of this article. The integral mode of the controller is the last term of the equation. Its function is to integrate or continually sum the controller error, e(t), over time. Some things we should know about the reset time tuning parameter, Ti: ▪ It provides a separate weight to the integral term so the influence of integral action can be independently adjusted. ▪ It is in the denominator so smaller values provide a larger weight to (i.e. increase the influence of) the integral term. ▪ It has units of time so it is always positive. Function of the Proportional Term As with the P-Only controller, the proportional term of the PI controller, Kc·e(t), adds or subtracts from CObias based on the size of controller error e(t) at each time t. As e(t) grows or shrinks, the amount added to CObias grows or shrinks immediately and proportionately. The past history and current trajectory of the controller error have no influence on the proportional term computation. The plot below (click for a large view) illustrates this idea for a set point response. The error used in the proportional calculation is shown on the plot: ▪ At time t = 25 min, e(25) = 60–56 = 4 ▪ At time t = 40 min, e(40) = 60–62 = –2 Recalling that contr
offset. The algorithm for a purely proportional controller is: or, expressed in deviation variables, the equation becomes: the Bias term disappears in this form because it is a constant. Proportional control of a first order process As an example, lets take a generic linear first order process expressed in deviation variables, with a single manipulation and single disturbance variable: y is the controlled variable, u the manipulated variable and d the disturbance. Km and Kd are the steady-state gains on the manipulation and disturbance variables. If the controller isn't connected to the manipulation ( the process is open-loop ), the process will respond to a step change in the disturbance in a standard first-order manner. The final change in the output will be Kdd*(the change in the disturbance times the gain) and the system will take around 5*tau to reach steady-state. If, however, a proportional controller is connected to the manipulation the following results: The final equation ends up as a standard form first-order differential equation - adding proportional control hasn't changed the type of response that we will obtain. What has changed is the time constant of the process which has been reduced by a factor of (1+Km Kc), the steady-state gain on the disturbance which has also been reduced by a factor of (1+Km Kc), and an extra term has been added to reflect the response to changes in the setpoint. The subscripts 'CL' mean that the terms represent the process' closed loop response - the response when the controller is connected to the process and the feedback loop is closed. Now, let's look at what happens when the disturbance changes by a step. The process is standard first-order so we already know what the shape of the response will be. The final change in the controlled output will be : NOTE THAT PROPORTIONAL CONTROL HAS NOT ELIMINATED THE EFFECT OF THE DISTURBANCE. This is a 'feature' of proportional control which will be discussed below. What proportional control has done is to reduce the disturbance's effect by a factor of (1+Km Kc). As the controller ga