Rotor Resistance Estimation of Vector Controlled Induction Motor Drive using GA/PSO tuned Fuzzy Controller

Induction motor with indirect field oriented control is preferred for high performance applications due to its excellent dynamic behavior. However, it is sensitive to variations in rotor time constant, especially variation in rotor resistance which needs to be estimated online. Conventionally the model reference adaptive system with fuzzy logic controllers as adaptation is used, which works satisfactorily for one particular operating condition and fails under variable operating condition. Therefore the need arises for a fuzzy controller whose parameters are tuned using evolutionary algorithm. In this paper, the input/output gain and the membership function parameters of the fuzzy system are optimized using genetic algorithm and particle swarm optimization to obtain an optimal designed fuzzy controller for rotor resistance estimation. The system is investigated in MATLAB/Simulink environment. Results shows that the steady state error in estimation of rotor resistance by the proposed controller under stringent operating condition is better with the proposed controller as compared to the conventional trial and error based fuzzy controller. Index Terms: Induction motor (IM), Indirect Rotor flux Field Oriented Vector Control (IRFOC), Rotor Flux Model Reference Adaptive system (RF-MRAS), Proportional Integral (PI) controller, Mamdani fuzzy controller, Genetic Algorithm (GA), Particle Swarm Optimization (PSO).

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