A neuro-fuzzy approach for stator resistance estimation of induction motor

• Main Authors: Jaalam, Norazila, Ahmed Haidar, Ahmed Mohamed, Ramli, Noor Lina, Nor Laili, Ismail
• Format: Research Report
• Language: English
• Published: 2011
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/36482/1/A%20neuro-fuzzy%20approach%20for%20stator%20resistance%20estimation%20of%20induction%20motor.wm.pdf; http://umpir.ump.edu.my/id/eprint/36482/

During the operation of induction motor, stator resistance changes incessantly with the temperature of the working machine. This situation may cause an error in rotor resistance estimation of the same magnitude and will produce an error between the actual and estimated motor torque which can leads to motor breakdown in worst cases. Therefore, this project will propose an approach to estimate the changes of induction motor stator resistance using neuro-fuzzy. Then, it will be compared with conventional method like PI estimator to see the effectiveness. The behaviour of the induction machine will be analyzed when the stator resistance is changed. Based on the changes, a corrective procedure will be applied to ensure the stabilities of the induction motor. Generally, this project can be divided into three main parts which are design of induction motor, design of neuro-fuzzy and PI estimator, and corrective procedure for the induction machine. The Newcastle Drives Simulation Library will be used to design the induction motor model and MATLAB SIMULINK will be used to design the stator current observer. The neuro-fuzzy estimator will be designed based on Sugeno Method Fuzzy Inference System.