A Novel Hybrid Backstepping and Fuzzy Control for Three Phase Induction Motor Drivers

High-performance three-phase induction motor drives face persistent challenges regarding nonlinear dynamics, load disturbances, and parameter variations, which limit response time, overshoot, and steady-state accuracy in industrial applications. This study aimed to determine whether a hybrid backstepping–fuzzy speed controller could quantitatively improve field-oriented control performance of induction motor drives compared with conventional fixed-gain backstepping and proportional–integral strategies. A mathematical model of an indirect field-oriented controlled induction motor was formulated in the synchronous reference frame, and a Lyapunov-based backstepping outer speed loop was derived with virtual current control inputs. Fuzzy logic was employed online to adapt the key backstepping coefficients based on speed error magnitude, while maintaining integral terms for load torque compensation. The proposed controller was implemented and evaluated in MATLAB/Simulink under step speed commands, speed reversals, and sudden load torque variations. Simulation results showed that the hybrid controller reduced speed overshoot from more than 12% with classical backstepping to 0%, while decreasing 2% settling time by approximately 35% and steady-state speed error to below 0.2%. Under a 50% rated load step, speed deviation remained within 1.5% and recovered in less than 0.08 s, compared with deviations above 5% and recovery times exceeding 0.15 s for conventional designs. These improvements indicate that the proposed strategy provides faster, more robust speed tracking with reduced mechanical stress, making it suitable for high-performance industrial induction motor drive applications.