AI Summary & Key Takeaways
AI InsightThe success of the proposed control algorithm has been experimentally tested by operating the induction motor under different speed and load conditions
📌 3 Key Takeaways
Abstract
There are difficulties in control of induction motors which are widely used in industrial applications due to their nonlinear complicated structures. Nowadays the use of advanced control methods along with technological progress has made it possible to achieve high performance in the control of these motors. Thanks to its nonlinear and adaptive structure, artificial neural network based control algorithms will be a suitable and efficient method for control of induction motors. In this study, the speed control of three-phase squirrel cage induction motor was implemented using the dsPIC30F6010A microcontroller. In order to improve the performance of the drive system, a speed control algorithm has been developed using a radial basis function artificial neural network based model reference adaptive control method. The success of the proposed control algorithm has been experimentally tested by operating the induction motor under different speed and load conditions
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