Fuzzy Logic based Speed Control of an Induction Motor Using Indirect Vector Control Method

Efficiency optimization of motor drives is very important not only from the viewpoints of energy loss and hence cost saving, but also from the perspective of environmental pollution. Several efficiency optimization methods for induction motor (IM) drives have been introduced nowadays by researchers. Distinctively, artificial intelligence (AI)-based techniques, in particular Fuzzy Logic (FL) one, have been emerged as a powerful alternative to conventional methods. Design objectives that are mathematically hard to express can be incorporated into a Fuzzy Logic Controller (FLC) using simple linguistic terms. The merit of FLC relies on its ability to express the amount of ambiguity in human reasoning. When the mathematical model of a process does not exist or exists with uncertainties, FLC has proven to be one of the best alternatives to move with unknown process.

In this paper, an implementation of intelligent controller for speed control of an induction motor (IM) using indirect vector control method has been developed and analyzed in detail. The project is complete mathematical model of field orientation control (FOC) of induction motor and simulated in MATLAB for studies of a 50 HP, squirrel cage type induction motor has been considered. The comparative performance of Fuzzy Logic control technique has been presented and analyzed in this work. The present approach avoids the use of flux and speed sensor which increase the installation cost and mechanical robustness. The fuzzy logic controller is found to be a very useful technique to obtain a high performance speed control. The indirect vector controlled induction motor drive involves decoupling of the stator current in to torque and flux producing components.

Keywords:  Induction motor(IM) drive,  Indirect Vector Control of Induction Motor(IVCIM),  Fuzzy Logic Controller(FLC),Field Oriented Control(FOC), Matlab,Fuzzy Inference System(FIS), Simulink model