Hybrid fuzzy control solutions for Brushless DC drives with Variable Moment of Inertia

This paper proposes four hybrid Takagi-Sugeno fuzzy controllers which consist of two hybrid PI Neuro-Fuzzy Controllers and two Adaptive Sliding Mode Fuzzy Controllers, for speed and position control of Brushless Direct Current motor (BLDC-m) drives. Simplified models of BLDC-m drives are derived and used in the new controller design; these models are characterized by second-order transfer functions with variable parameters and with or without an integral component. The proposed controllers and systematic design methodologies are briefly presented and some particular approaches are highlighted. The control structures exhibit important robustness properties proved by simulation results. The design methodologies guarantee the system stability and offer consistent performance under model uncertainties. Simulation-based comparisons illustrate the efficiency of the controllers.