Process variable

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In control theory, a process variable (PV; also process value or process parameter) is the current measured value of a particular part of a process which is being monitored or controlled. An example of this would be the temperature of a furnace. The current temperature is the process variable, while the desired temperature is known as the set-point (SP). [1]

Control system use

Block diagram of a negative feedback control system used to maintain PV = SP Set-point control.png
Block diagram of a negative feedback control system used to maintain PV = SP

Measurement of process variables is essential in control systems to controlling a process. The value of the process variable is continuously monitored so that control may be exerted.

Four commonly measured variables that affect chemical and physical processes are: pressure, temperature, level and flow.[ citation needed ] but there are in fact a large number of measurement quantities which for international purposes use the International System of Units (SI)

The SP-PV error is used to exert control on a process so that the value of PV equals the value of the SP. A classic use of this is in the PID controller.

Related Research Articles

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Observational error is the difference between a measured value of a quantity and its true value. In statistics, an error is not necessarily a "mistake". Variability is an inherent part of the results of measurements and of the measurement process.

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A proportional–integral–derivative controller is a control loop mechanism employing feedback that is widely used in industrial control systems and a variety of other applications requiring continuously modulated control. A PID controller continuously calculates an error value as the difference between a desired setpoint (SP) and a measured process variable (PV) and applies a correction based on proportional, integral, and derivative terms, hence the name.

<span class="mw-page-title-main">Sensor</span> Converter that measures a physical quantity and converts it into a signal

A sensor is a device that produces an output signal for the purpose of sensing a physical phenomenon.

<span class="mw-page-title-main">Control system</span> System that manages the behavior of other systems

A control system manages, commands, directs, or regulates the behavior of other devices or systems using control loops. It can range from a single home heating controller using a thermostat controlling a domestic boiler to large industrial control systems which are used for controlling processes or machines. The control systems are designed via control engineering process.

In control theory, an open-loop controller, also called a non-feedback controller, is a control system in which the control action is independent of the "process output", which is the process variable that is being controlled. It does not use feedback to determine if its output has achieved the desired goal of the input command or process setpoint.

An industrial process control in continuous production processes is a discipline that uses industrial control systems to achieve a production level of consistency, economy and safety which could not be achieved purely by human manual control. It is implemented widely in industries such as automotive, mining, dredging, oil refining, pulp and paper manufacturing, chemical processing and power generating plants.

<span class="mw-page-title-main">Setpoint (control system)</span> Target value for the process variable of a control system

In cybernetics and control theory, a setpoint is the desired or target value for an essential variable, or process value (PV) of a control system. Departure of such a variable from its setpoint is one basis for error-controlled regulation using negative feedback for automatic control.

<span class="mw-page-title-main">Proportional control</span> Linear feedback control system

Proportional control, in engineering and process control, is a type of linear feedback control system in which a correction is applied to the controlled variable, and the size of the correction is proportional to the difference between the desired value and the measured value. Two classic mechanical examples are the toilet bowl float proportioning valve and the fly-ball governor.

<span class="mw-page-title-main">Rheometer</span> Scientific instrument used to measure fluid flow (rheology)

A rheometer is a laboratory device used to measure the way in which a dense fluid flows in response to applied forces. It is used for those fluids which cannot be defined by a single value of viscosity and therefore require more parameters to be set and measured than is the case for a viscometer. It measures the rheology of the fluid.

Condition monitoring is the process of monitoring a parameter of condition in machinery, in order to identify a significant change which is indicative of a developing fault. It is a major component of predictive maintenance. The use of condition monitoring allows maintenance to be scheduled, or other actions to be taken to prevent consequential damages and avoid its consequences. Condition monitoring has a unique benefit in that conditions that would shorten normal lifespan can be addressed before they develop into a major failure. Condition monitoring techniques are normally used on rotating equipment, auxiliary systems and other machinery, while periodic inspection using non-destructive testing (NDT) techniques and fit for service (FFS) evaluation are used for static plant equipment such as steam boilers, piping and heat exchangers.

<span class="mw-page-title-main">Thermodynamic instruments</span>

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In thermodynamics, work is one of the principal processes by which a thermodynamic system can interact with its surroundings and exchange energy. An exchange of energy is facilitated by a mechanism through which the system can spontaneously exert macroscopic forces on its surroundings, or vice versa. In the surroundings, this mechanical work can lift a weight, for example.

A control loop is the fundamental building block of industrial control systems. It consists of all the physical components and control functions necessary to automatically adjust the value of a measured process variable (PV) to equal the value of a desired set-point (SP). It includes the process sensor, the controller function, and the final control element (FCE) which are all required for automatic control.

<span class="mw-page-title-main">Temperature</span> Physical quantity that expresses hot and cold

Temperature is a physical quantity that expresses the hotness of matter or radiation.

<span class="mw-page-title-main">Instrumentation in petrochemical industries</span>

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Industrial process data validation and reconciliation, or more briefly, process data reconciliation (PDR), is a technology that uses process information and mathematical methods in order to automatically ensure data validation and reconciliation by correcting measurements in industrial processes. The use of PDR allows for extracting accurate and reliable information about the state of industry processes from raw measurement data and produces a single consistent set of data representing the most likely process operation.

Sensors for arc welding are devices which – as a part of a fully mechanised welding equipment – are capable to acquire information about position and, if possible, about the geometry of the intended weld at the workpiece and to provide respective data in a suitable form for the control of the weld torch position and, if possible, for the arc welding process parameters.

<span class="mw-page-title-main">Photovoltaic system performance</span>

Photovoltaic system performance is a function of the climatic conditions, the equipment used and the system configuration. PV performance can be measured as the ratio of actual solar PV system output vs expected values, the measurement being essential for proper solar PV facility's operation and maintenance. The primary energy input is the global light irradiance in the plane of the solar arrays, and this in turn is a combination of the direct and the diffuse radiation.

References

  1. B. Wayne Bequette (2003). Process Control: Modeling, Design, and Simulation. Prentice Hall Professional. p. 5. ISBN   9780133536409.