A Comparison of Induction Motor Speed Estimation using Conventional MRAS and AI- Based MRAS with a Dynamic Reference Model
نویسندگان
چکیده
− The Model Reference Adaptive System (MRAS) is probably the most widely applied speed sensorless drive control scheme. This paper compares induction motor speed estimation using conventional MRAS and AI-based MRAS with Stator Resistance Compensation. A conventional mathematical model based MRAS speed estimation scheme can give a relatively precise speed estimation result, but errors will occur during low frequency operation. Furthermore, it is also very sensitive to machine parameter variations. However, an AI-based MRAS-based system with a Stator Resistance Compensation model can improve the speed estimation accuracy and is relatively robust to parameter variations even at an extremely low frequency. Simulation results using a validated machine model are used to demonstrate the improved behaviour. Index Terms− Dynamic Reference Model, Model Reference Adaptive System (MRAS), Neural Networks, Induction Motor Control.
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