Control System

Types of Control Loops

What is a Control Loop?

  • Control loop systems are used in industrial or manufacturing processes, and their primary function is to monitor and control the many machines, instruments, and devices that are involved in these processes.
  • The system runs the hardware parts and software control functions that are needed to measure and adjust the variables that affect each process.
  • As a process management technique intended to keep the process variable at a specified set point at each step, think of control loop systems.
  • Process variables are a group of programmable factors used to monitor and regulate a process in order to keep the output within a predetermined range or amount.
  • Instrumentation and components of the control loop first measure the variable, react to it, and then regulate the variable to keep it within a predetermined limit.

The control loops used in the process control industry all function in the same manner, which necessitates the completion of the following three tasks:

  1. Measurement
  2. Comparison
  3. Adjustment

What are Different Types of Control Loops?

In industrial operations, two types of control loop systems are often utilised. They are the closed loop system and the open loop system, respectively. The control actions serve as a key differentiator between the systems.

Open Loop Control System

Open loop control is a type of control in which the action taken by the controller is not dependent on the “process output” (or “controlled process variable” – PV). In a control system with an open loop, the actions of the controller are not dependant on the intended output. This means that the output is not monitored and is not fed back to the input for comparison.

Open Loop Control System

When a command is given to a controller, it sends out a signal to take action. This controlling signal is put into a process that needs to be controlled, and that process then makes the output that was desired. Open loop systems don’t have any checks and balances because they don’t have a feedback system. This means that the system is expected to follow the input command no matter what the end result is.

Also referred to as a control system without feedback, an open loop control system. The control action in open loop systems is independent of the intended output.

Example of Open Loop Control Systems

Examples of Open Loop Control Systems

Closed Loop Control System

Closed Loop Control System

Closed-loop control systems are also referred to as feedback control systems.

In closed loop control systems, the action taken to control something depends on what you want the output to be.

In closed loop control systems, the output is compared to the reference input, and an error signal is made. The error signal is then sent to the controller to reduce the error and get the desired output.

Closed-loop control systems 1

A feedback loop is an essential component of a closed-loop controller. This loop assures that the controller will always perform a control action to keep a process variable at the same value as the setpoint. Closed-loop controllers are also sometimes referred to as feedback controllers due to this reason.

The error is a function that is applied to the controller’s output in a closed loop. The difference between the process variable and the set point is referred to as the error, and it is calculated as E = SP – PV. Error is defined as the deviation of the process variable from the set point.

These systems are more dependable, quicker, can handle a greater number of variables simultaneously, and can be optimized.

Example of Closed Loop Control Systems

Examples of Closed Loop Control Systems

From the controller’s point of view, the process includes the RTD, the steam control valve, and signal processing of the PV and CO values.

Linear Control Systems

Linear control systems employ negative feedback to provide a control signal that keeps the regulated PV at the target SP. There are several varieties of linear control systems, each with unique abilities.

Proportional Control

Proportional control is a type of linear feedback control system in which a correction is made to the controlled variable that is proportional to the difference between the desired value (SP) and the measured value (PV).

A control signal is provided by Proportional control, and its amplitude and direction are proportional to those of the error signal.

When there is a disruption, the Proportional control system will simply supply a new mass balance scenario. When there is a change in the control signal, there must also be a change in the error signal; as a result, there will be an offset. A error is stabilized by Proportional control; it is not eliminated.

  • M=Measure signal or process variable (PV)
  • SP=set point
  • e(error)= SP -M
  • m= controller signal output
  • k= gain
  • b=bias
  • m=ke+ b
  • PB=proportional band
  • Gain(k)=100%/PB

Proportional band is defined as that input signal span change, in percent, which will cause a hundred percent change in output.

On-off control is suitable for systems with low accuracy or responsiveness requirements, but it is inefficient for quick adjustments and reactions. In order to overcome this, proportional control modulates the process variable (PV), such as a control valve, at a gain level that prevents instability while yet delivering correction as quickly as is practical.

Here, e = SP – PV denotes a loop with a reversal action. A direct-acting loop is referred to when e = PV – SP. The output should be increased by the controller in a direct-acting loop since the process variable is larger than the set point. A system that regulates temperature using cooling water is an example of a direct-acting system. In a reverse-acting loop, the output is decreased by the controller because the process variable is lower than the set point. An example would be a steam-based temperature control system.

The proportional control shown in the next picture demonstrates how there is always a steady state inaccuracy. As the proportional gain is increased, the inaccuracy will be less, but oscillation tendencies will also grow.

Proportional Control

Integral Control

Integral control seeks to overcome the first problem with proportional control by resolving a minor inaccuracy (offset). The integral looks at the inaccuracy over time and amplifies even a little error over time. The integral is equal to the error multiplied by the whole amount of time that the error has been present.

At time zero, a little error has no consequence. A little error at time 10 has a consequence equal to a 10 times error. As a result, the integral makes the system more responsive to a particular issue over time until it is corrected. Additionally, the integral may be adjusted; this adjustment is known as the reset rate.

The reset rate is a factor of time. The speed of error correction increases with the decrease in reset rate. A reset rate that is too high, however, might result in inconsistent performance. A potentiometer that modifies an RC circuit’s time constant may be used to adapt hardware-based systems. The majority of systems used nowadays employ software-based controls, including PLC modules that allow engineers to alter the reset rate’s parameter.

Integral Control


  • Iout: Integral portion of controller output 
  • Ti : Integral time, or reset time 
  • Ki : Integral gain

Error signal, e = Set point(SP) – Process variable(PV)

The controller can drive the error to zero since it may adjust its output as long as the problem persists. There is a slower reaction time (compared to P-only mode)

Integral Control

It combines the most advantageous aspects of the proportional and integral modes.

With minimal loss of reaction speed, the proportional offset is removed.

Integral Control

Derivative Control

The derivative portion of the control output makes an effort to examine the error signal’s rate of change. A high rate of change will result in a stronger system reaction from the derivative than a slow rate of change. In other words, if a system’s error keeps increasing, the controller must not be making enough corrections in response.

The derivative gives a stronger reaction since it can detect how quickly the error is changing. The derivative is also known as rate time since it is time-adjusted. It is crucial to avoid applying too much derivative since this might lead to overshoot or inconsistent control.

The derivative term (Dout) is denoted mathematically as follows:

Derivative Control 1
  • Dout: : The controller’s derivative output
  • Derivative gain is Td
  •  Derivative time is  Kd
  • e is  Error signal
  • e is the set point minus the process variable.(SP-PV)
Derivative Control 2

The majority of the time, they are seen in conjunction with proportional control and other control components.

PD controller’s reaction to a ramp change in error

An offset may be produced using PD control.

The bias “b” should be set  to prevent proportional offset.

Temperature, pH, and composition controls are examples of typical slow-response process controls.

PID control

Tasks performed by all three controls, proportional control changes an input signal in a direct proportion to the variance in the error signal. It reacts instantly to the current tracking error, but without an intolerably high gain, it is unable to reach the required set point consistency. The proportional term often requires the other components as a response. The output signal changes under integral control as a function of the integral of the error signal over time. When monitoring a fixed set point, the integral term produces zero steady state error. Additionally, it opposes ongoing disruptions. Derivative action eliminates transient errors and modifies an output signal in accordance with the rate at which the error signal is changing. 

The control output, also known as the control variable, will be determined based on the contributions of the three terms:

Control Variable = Pout + Iout + Dout

The diagram that follows provides an illustration of a closed-loop system that has integral, proportional, and derivative control.

PID control 1

Examples of Linear Control Systems(PID)

Examples of Linear control systems(PID)

ON-OFF Control

ON-OFF Control 1

On-off control employs a feedback controller that quickly shifts between two states. In response to an error, on-off control gives the controller an output of either ON or OFF. When the controller output changes direction, deadband is the value that must be reached before the controller output changes direction again.

ON-OFF Control 1 2

Analog or Continuous System

In this category of control systems, the input to the system is represented by a signal that is continuously present. The continuous function of time is represented by these signals. We may have a number of different sources of continuous input signal, such as a source of sinusoidal type signals, a source of square type signals, or the signal could be in the shape of a continuous triangle, among other possible forms.

What are the 4 basic elements in process control system?

Knowledge of these four fundamental components is necessary to successfully regulate a process: 

What are the 4 basic elements in process control system?
  • The process itself
  • The sensor that determines the value of the process
  • The final control element that modifies the variable that is being managed
  • The controller.

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