Speed Control Of Dc Motor Using Fuzzy Logic Thesis

Speed Control Of Dc Motor Using Fuzzy Logic Thesis-30
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The speed control of Brush Less DC motor is control by Neural Network method more efficiently and provided stability to the different applications.

In case of DC motor category there are two types of motors available in the market.

In Brush Less DC motor there is no physical commutator present in the inner part of the machine.

The dynamic model of Brush Less DC motor shown in the figure 1.

The names of the two motors are Permanent magnet synchronous motor and Permanent Magnet Brush less DC motor.

The EMF production in these motors are in backward manner [1].A Brush Less DC motor is operated by the direct current (dc) which having the automatically controlled commutation system instead of mechanically controlled commutation present in the synchronous motor.It is also known as the trapezoidal Permanent Magnet motor because of their output waveform shapes.The topics to be covered include, but are not limited to: Control of linear/nonlinear systems, Stability, Controllability and Observations, Modelling Estimation and Prediction, Real-Time Systems control, Real-Time and Fault-Tolerant Systems, Multidimensional Systems control, Large Scale Control Systems, Robust Control, Intelligent Control Systems; Stochastic Control, Fuzzy Control Systems, Neuro-Controllers, Neuro-Fuzzy Controllers, Genetic Algorithms, Adaptive Control Techniques.The applications concern control methods, modelling and identification of processes in the fields of industry, ecology, natural resources, comprising physical, biological and organizational systems.Here, we discuss the Fuzzy Logic Control of the speed of DC Motor.We make use of this this strategy to achieve a flexible control of the speed of the Separately Excited DC Motor.They include but are not limited to: Power System Control, Control of electrical drives, Automotive Control Systems, Control of Power Electronics, Automatic Control of Chemical Processes, Thermal System Control, Robot and Manipulator Control, Aerospace Control Systems, Motion and Navigation Control, Traffic and Transport Control, Defense and Military Systems Control, Nuclear systems control, Control and analysis of Social and Human Systems, Biomedical control systems.IREACO also publishes letters to the Editor and research notes which discuss new research, or research in progress in any of the above thematic areas.In this thesis the Brush less DC motor speed is controlled by the Neural Network.The Neural Network tuned Brush Less DC motor speed is controlled via PI gain parameters optimal selection.


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