# Motor Generation System

**Topics:**Control theory, Electric motor, Electrical engineering

**Pages:**7 (2222 words)

**Published:**March 17, 2014

Introduction:

A control system generally controls, regulates, and updates its output continuously based on present inputs, nature of the system, and the past outputs. In other words, there is a feedback mechanism that is inherent in the system, and is called a closed loop control system. For example, adding an emitter resistance to a common emitter amplifier, results in a negative feedback mechanism in the amplifier system – if the output current increases, the input voltage decreases accordingly so as to reduce the output current; if the output current decreases, then the input voltage increases in order to raise the output current level. Negative feedback thus ensures that the output is always controlled to stay within an optimal range. Similarly other systems may exhibit a positive feedback mechanism. In either case, a control system can be represented as follows:

Figure 1: Control System representation

In Figure 1, G represents the forward loop function and Fb represents the feedback function. In case the Fb function is absent, the system is reduced to an open loop system.

The most popular representation of control systems is using the ‘Block Diagram’ approach (Balakrishnan, 1988). Each component in the system is represented as a block, with its role represented as a mathematical function. From the block diagram representation, the overall function of the system, called the transfer function, is obtained. The transfer function of a system is defined as , where and denote the output and input functions of the system respectively, denoted in Laplace form. It is important to note that for Transfer system analysis, the initial conditions need to be zero. Further, the transfer function model does not support analysis of Multiple Input Multiple Output (MIMO) systems, where modelling becomes very complicated.

The disadvantages associated with the transfer function model led to the state space model, where the system is represented by means of the smallest number of variables associated with the system, which can completely describe it at any instant. For a linear, time invariant system, the general state space representation is as follows:

Where is the state vector (column vector) that comprises the state variables , and so on; is the input vector, and is the output vector; and represents the differentiation of each component of the sate vector, with respect to time (Kamaraju, Narasimham, 2009). All automated systems are control systems with complex feedback and regulatory mechanisms. The design of such systems involves a clear understanding of representation of various parameters associated with the system, how they affect the outputs, and the effect of presence of any external disturbances to the system performance. These parameters contribute to the stability of the system, which is the most important design factor.

Essentially, the physical components in a control system depend on the nature of the system, in terms of functionality and stability, and in terms of its surroundings. Depending on the nature of the components in the system, the system can be classified as electrical, mechanical, electromechanical, digital, and other control systems. For example, a complex system consisting of motors and other electrical drives to carry our electrical operations, using mechanical components such as shafts can be termed as an electromechanical system. Most of the motion control systems are electromechanical systems. An important part of a motion control system, is speed control. Unlike fully mechanical or hydraulic speed controls, electric speed controls are capable of varying the speed of the electric motor itself. Majority of electrical variable speed drives, also known as VSDs are compatible with the 3-phase AC power supply. The two most popular electrical VSDs that were originally designed as an AC commutator motor and DC motor generator were the Schrage motor...

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