Artificial Intelligence Based Dynamic Simulation of Induction Motor Drives

Induction Motors have many applications in the industries, because of the low maintenance and robustness. The speed control of induction motor is more important to achieve maximum torque and efficiency. This paper presents an integrated environment for speed control of vector controlled Induction Motor (IM) including simulation. The integrated environment allows users to compare simulation results between classical and artificial intelligent controllers. In recent years, the field oriented control of induction motor drive is widely used in high performance drive system. It is due to its unique characteristics like high efficiency, good power factor and extremely rugged nature of Induction motor. 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 speed control scheme of vector controlled induction motor drive involves decoupling of the speed and reference speed into torque and flux producing components. The performance of fuzzy logic and artificial neural network based controller's is compared with that of the conventional proportional integral controller. The dynamic modeling of Induction motor is done and the performance of the Induction motor drive has been analyzed for constant and variable loads.