Category: Control Systems
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Key Causes of Uncertainty in Control Systems
One of the objectives of a control system is to achieve good plant performance in the face of uncertainty. The major sources of uncertainty in control are: Unmeasurable Perturbations Unmeasurable perturbations produce output deviations. With a controller in place, the achieved deviations must be below a user-defined bound. Modelling Errors Modelling errors can be classified…
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Centralised vs. Decentralised Control Systems
Centralised control is usually carried out via computer software, having as inputs all the available sensors and producing signals for all the available actuators in the system. This control strategy is the most powerful, at least in theory, capable of extracting “optimal” performance. However, in practice, it requires non-standard apparatus (industrial computer data acquisition cards,…
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Adaptive Control System
Adaptive control system adjusts to changes and modifies its parameters to fit the prevailing circumstances. The adaptive control system is based on the use of a microprocessor as the controller. Such a device enables the control mode and the control parameters employed to be adapted to fit the prevailing circumstances, modifying them as the circumstances…
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Control Modes in Automation Systems
The mode of control is the way in which a control system makes corrections relative to an error that exists between the setpoint of a controlled variable and its actual value. We have a number of ways (i.e. control modes) by which a control unit can react to an error signal and supply an output…
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The Performance Limits for PID Controllers
PID Controllers can be applied successfully to most control problems in process control, electrical drive systems and servo mechanisms due to the fact that most of these processes have a dynamic behaviour that can be adequately approximated by a second-order process. However, the PID controller is not enough to control processes with additional complexities like…
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What is Selective Control?
In a number of process control problems, we may have more measurements (controlled variables) than manipulated variables. Hence, it is impossible to eliminate errors in all the controlled variables for arbitrary setpoint changes of disturbances by using only simple (single-input/single output) controllers. Thus selectors are used to share the manipulated variables among the controlled variables.…
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5 Control Techniques – Their Features & Applications
We have a number of control theories that have been put forward on how to design control laws to accomplish various purposes. Generally they can be classified as follows: Classical Control This control technique deals with the behaviour of dynamical systems, which typically have inputs and how their behaviour is modified by feedback, employing the…
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Hierarchical Control Strategies for a Process Plant
In a process plant, we typically have a number of control goals that require different algorithms and types of information from the process; from the level closest to the process to the plant-wide control. All these activities ought to be connected; hence some kind of hierarchy is necessary. Local Control Local control uses information directly…
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What is a Discontinuous Controller?
This is a controller with only 2 switching states, that is, the output signal is switched ON and OFF depending on whether the process variable goes below or above a preset limit or setpoint. An example of a discontinuous controller is a resistance thermometer (Pt 100), whose electronic circuitry switches heating on if the temperature…
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Analog vs. Digital Controllers
Analog signals pass continuously through a full range of values for example a measuring device converts the process variable (PV), say temperature, into a signal corresponding to this temperature. Each temperature value corresponds to a value of the electrical signal. Digital signals belong to the group of discrete signals; here the individual signals are represented…