This paper presents an adaptive Fractional Order PID (FOPID) controller for improving the performance of a Brushless DC (BLDC) motor using Artificial Bee Colony (ABC) algorithm. BLDC motor is desired to operate at various speed and load conditions with enhanced performance and robust speed control. In practice, the effect of longer settling time, fluctuation of steady-state error, power fluctuation and nonlinearity characteristics of the BLDC motor drive result in poor controllability. To

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... me the problems, an optimized FOPID controller using the ABC algorithm in a self-tuned regulator structure is proposed to minimize the given objective function to satisfy the inequality constraints. It is also interesting to note that the usage of Hall Effect sensors has many limitations due to the failure of its components, poor reliability, need special mechanical arrangements for mounting and electrical noise aspects. In order to avoid such issues, a Kalman Filter is designed for estimating the speed of the motor. The simulation is carried out for the proposed ABC tuned FOPID controller and the results are compared with conventional genetic algorithm and modified genetic algorithm tuned FOPID controllers. The results indicate that the proposed ABC tuned controller is superior in terms of time-domain characteristics, control effort, and specified performance indices. Further to show the usefulness of the proposed method, an experimental model is developed and validated for the selected operating conditions with the required comparison. J o u r n a l P r e -p r o o f Journal Pre-proof parameters (Kp, Ki, Kd, λ, and μ) which are complex for tuning, and hence optimization methods are needed to obtain the optimal solution. Tuning of FOPID controller to meet the given error indices such as Integral Square Error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Error (ITAE) are also gaining attention for researchers working in the area of fractional J o u r n a l P r e -p r o o f Journal Pre-proof Highlights  A constrained optimization problem is presented to update the FOPID controller using the ABC algorithm for sensorless speed control of BLDC in the self-tuning regulator structure. The proposed tuning method minimizes the time domain specifications in addition to the error indices such as IAE, ITAE, and ISE under varying load and set speed conditions.  To avoid the speed sensors, a Kalman filter method is used for estimating the speed of the motor.  A Simulink model of an ABC optimized FOPID controller for sensorless speed control of BLDC motor is developed.  The detailed simulation is conducted for the proposed ABC tuned FOPID controller and the results are compared with CGA and MGA tuned FOPID controllers. The results indicate that the ABC tuned controller is better in terms of time domain characteristics, control effort, and specified performance indices.  Further to show the usefulness of the proposed controller design, an experimental model is developed, validated for selected operating conditions, and the results are compared with simulation results. J o u r n a l P r e -p r o o f Journal Pre-proof