Switched Reluctance Machine fuzzy modeling applied on a MRAC scheme

This paper proposes an approach for modeling a Switched Reluctance Machine with fuzzy logic. The proposed model is verified under a Model Reference Adaptive Control scheme. Calculating Fuzzy Inference Systems instead of the nonlinear terms of state equations decreases the model complexity and computing costs, which is important for the MRAC scheme, and provides a mathematical model for adaptive control. Amodel architecture is presented where linear equations interact with a Fuzzy Inference System. An angular speed control experiment was successfully simulated using the resulting fuzzy model as reference.