Direct Field-Oriented Control of an Induction Motor Using Fuzzy Logic Speed Controller

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This paper presents a direct field-oriented control (DFOC) scheme for a squirrel-cage induction motor in which the outer speed control loop is implemented using a Mamdani-type fuzzy logic controller with a full 49-rule base. The proposed approach aims to enhance dynamic performance and robustness of induction motor drives operating under nonlinear characteristics, parameter variations, and rapid load or speed changes. In the adopted rotor-flux-oriented DFOC architecture, the fuzzy speed controller utilizes the speed error and its derivative as input variables and directly generates the reference value of the torque-producing stator current component in the synchronous reference frame. Seven linguistic terms are employed for each input and output variable, resulting in a finely shaped nonlinear control surface capable of providing aggressive control action during large transients and smooth regulation near steady-state conditions. The complete drive system is modeled and implemented in MATLAB Simulink, including the inverter, induction motor, and control system. Simulation results demonstrate fast and well-damped speed responses for step changes in reference speed, reliable four-quadrant operation, limited overshoot, and steady-state speed error maintained below approximately 1%. The results confirm that the proposed 49-rule fuzzy logic speed controller offers an effective and practical solution for high-performance DFOC induction motor drives, achieving a favorable trade-off between control accuracy, dynamic response, and controller complexity.