DocumentCode
255336
Title
Dynamic analysis & artificial intelligent control of induction motor drives
Author
Menghal, P.M. ; Laxmi, A.J.
Author_Institution
Fac. of Degree Eng., Mil. Coll. of Electron. & Mech. Eng., Secunderabad, India
fYear
2014
fDate
11-13 Dec. 2014
Firstpage
1
Lastpage
6
Abstract
Induction motors have many applications in the industries, because of the low maintenance and robustness. The speed control of induction motor is very important to achieve maximum torque and efficiency. In the same period, there were also advances in control methods and Artificial Intelligent (AI) techniques, including expert system, fuzzy logic, neural networks and genetic algorithm. Researchers soon realized that the performance of induction motor drives can be enhanced by adopting artificial-intelligent based methods. This paper presents an integrated environment for speed control of Induction Motor (IM) using artificial intelligent controller. The integrated environment allows users to compare simulation results between classical and artificial intelligent controllers. The fuzzy logic controller and artificial neural network controllers are also introduced to the system for keeping the motor speed to be constant when the load varies. The performance of fuzzy logic and artificial neural network based controllers´ is compared with that of the conventional proportional integral controller. The performance of the Induction motor drive has been analyzed for constant and variable loads.
Keywords
angular velocity control; fuzzy control; genetic algorithms; induction motor drives; machine control; neurocontrollers; AI techniques; artificial intelligent control; artificial neural network controllers; classical controllers; constant loads; dynamic analysis; expert system; fuzzy logic controller; genetic algorithm; induction motor drives; integrated environment; proportional integral controller; speed control; variable loads; Artificial neural networks; Fuzzy logic; Induction motor drives; Mathematical model; Torque; Fuzzy Logic Controller (FLC); Intelligent Controller Adaptive Neuro Fuzzy Inference System(ANFIS); Neural Network(NN); Proportional Integrator(PI) Controller;
fLanguage
English
Publisher
ieee
Conference_Titel
India Conference (INDICON), 2014 Annual IEEE
Conference_Location
Pune
Print_ISBN
978-1-4799-5362-2
Type
conf
DOI
10.1109/INDICON.2014.7030419
Filename
7030419
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