Control System: A boon for modern World

Mrs. Aabha Sahu

Assistant Professor - Department of Electrical Engineering Kalinga University, New Raipur

Control System, meaning by which a variable quantity or set of variable quantities is introduced to conform to a specified standard. Either it keeps the values ​​of the controlled quantities constant, or it changes them in a specified way. The control system may be actuated electrically, mechanically, by fluid pressure (liquid or gas), or by a combination of means. When a computer is involved in the control circuit, it is often more practical to operate all electrically controlled systems, although mixtures are quite common.

Development of control systems.

Control systems are closely related to the concept of automation (qv), but the two basic types of control systems, transmission and feedback, have classical origins. The loom invented by Joseph Jacquard of France in 1801 was an early example of a loom; a set of punch cards that program the patterns woven by the loom; no process information is used to adjust machine operation. Similar predictive control was introduced into some machine tools invented in the 19th century, where a tool cut to the shape of a pattern.

Feedback control, in which process information is used to adjust machine operation, has an even older history. Roman engineers maintained the water level in their aqueduct with floating valves that opened and closed at appropriate levels. 17th-century Dutch windmills are kept facing the wind by the action of an auxiliary vane that moves the entire upper part of the mill. The most famous example from the Industrial Revolution is James Watt’s flyball controller of 1769, a device that regulates the flow of steam to a steam engine to maintain a constant engine speed despite load. change.

The first theoretical analysis of control systems, which presented the differential equation model of governor Watt, was published by James Clerk Maxwell, the Scottish physicist, in the 19th century. Maxwell’s work. was quickly generalized and control theory was developed thanks to a number of contributions, including a remarkable study of the autopilot system of the American battleship “New Mexico”, published in 1922. The 1930s saw the development of lasting electrical feedback. telephony amplifier and general theory of servicing, whereby a small amount of power controls a very large amount and performs automatic corrections. Pneumatic control unit, the basis for the development of automated systems initially in the chemical and petroleum industries, and later on analog computers. All of these developments formed the basis for the development of control systems theory and applications during World War II, such as anti-aircraft batteries and fire control systems.


Most theoretical studies as well as practical systems up to World War II were a loop, i.e. they only involved feedback from a single point and correction from a single point. In the 1950s, the potential of many loop systems was investigated. In these systems, feedback can be made at many points in a process and corrections made from many points. The advent of analog and digital computer equipment paved the way for more complexity in automatic control theory, an advance since so-called “modern control” to distinguish it from ” classic controls” is older and simpler.

Basic principles.

With a few relatively minor exceptions, all modern control systems share two basic characteristics. They can be described as follows: (1) The value of the quantity to be controlled is changed by a motor (this word is used in a general sense), which derives its power from a local source. set and not from the incoming signal. Therefore, a large amount of power is available to make the necessary changes in the controlled quantity and to ensure that the controlled quantity change operations do not load and distort the signals that the accuracy of the quantity changes. The accuracy of the control depends on. (2) The rate at which the motor is energized to effect a change in the value of a controlled quantity is determined directly as a function of the difference between the actual value and the desired value of the controlled quantity. control. So, for example, in the case of an isothermal heating system, the amount of fuel supplied to the furnace is determined by whether the actual temperature is higher or lower than the desired temperature. A control system with these basic characteristics is called a closed-loop control system, or serving mechanism. An open-loop control system is a predictive system.

The stability of a control system is determined to a large extent by its response to a sudden or transiently applied signal. If such a signal causes the system to overcorrect, a phenomenon known as hunting can occur in which the system first overcorrects in one direction and then overcorrects in the opposite direction. again. Since hunting is undesirable, steps are often taken to correct it. The most common remedy is to add damping somewhere in the system. Shock absorbers slow down the system’s response and prevent over- or over-running. Shock absorbers can be in the form of resistance in an electronic circuit, the application of a brake in a mechanical circuit, or the force of oil through a small hole as in a shock absorber’s shock absorber.

Another method to check the stability of a control system is to determine its frequency response, i.e. its response to a continuously changing input signal at different frequencies. The output of the control system is then compared with the input in terms of amplitude and phase, i.e. the offset of the input and output signals. The frequency response can be determined experimentally – especially in electrical systems – or calculated mathematically if the system constants are known. Mathematical operations are especially useful for systems that can be described by ordinary linear differential equations. Graphical shortcuts also help a lot in studying system responses.

Several other techniques go into the design of advanced control systems. Adaptive control is the ability of a system to modify its own behavior to achieve the best possible mode of operation. The general definition of adaptive control implies that an adaptive system must be able to perform the following functions: provide continuous information about the current state of the system or define a process; compare the current performance of the system with the desired or optimal performance and make the decision to modify the system to achieve the defined optimal performance; and start making appropriate modifications to drive the control system to the optimum level. These three principles – define, decide, and modify – are inherent in any adaptive system.

Dynamically optimized control requires the control system to behave in such a way that a particular performance criterion is satisfied. This criterion is usually formulated in such a way that the controlled system must move from the original location to the new location in the minimum time possible or with minimum total cost.

Learning control implies that the control system has sufficient computing power that it can develop representations of the mathematical model of the controlled system and can modify its own behavior to take advantage of This newly developed knowledge. So the learning control system is a further development of the adaptive controller.

Non-interactive multivariate control involves large systems in which the size of internal variables depends on the values ​​of other relevant process variables. Therefore, the single-loop techniques of classical control theory will not suffice. More complex techniques must be used to develop control systems suitable for such processes.

Modern control practices.

There are various cases in industrial control practice where theoretical methods of automatic control are not yet advanced enough to design an automatic control system or to adequately predict the effects of an automatic control system. it. This situation holds true for very large, highly interconnected systems such as those found in many industrial facilities. In this case, operations research (qv), a mathematical technique for evaluating possible procedures in a given situation, can be useful.

To determine the actual physical control system to be installed in an industrial facility, the instrumentation or control system engineer has a variety of devices and methods that can be used. He may choose to use a similar toolkit of analog tools, those that use a continuously variable physical representation of the signal involved, i.e. current, voltage or barometric pressure . Devices built to handle such signals, often referred to as conventional devices, are capable of receiving a single input signal and performing output correction. Therefore, they are often thought of as single-loop systems and overall control systems consisting of a set of such devices. Analogue calculators are available that can consider multiple variables at once for more complex control functions. However, they are very specific in their applications and therefore are not commonly used.

The number of control devices added to an industrial installation can vary widely from plant to plant. They may include only some of the tools used primarily as indicators of plant operating conditions. As a result, the operator is aware of abnormal conditions and himself adjusts plant operating equipment such as valves and governors to maintain control. On the other hand, there can be devices of sufficient number and complexity that almost all possible scenarios can be accomplished by a command action that provides automatic control over everything. failures or disturbances are predictable and thus allow unattended process control.

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