This paper describes a simple way to control the Brushless DC (BLDC) motor for electrical applications. To control this machine, it is generally required to measure the speed and position of the rotor by using the sensor, because the inverter phases acting at any time must be commutated depending on the rotor position. Encoders and resolvers have been used for sensing the rotor position with respect to the stator. These sensors, however, make the motor system more complicated and mechanically unreliable. A method for the estimation of the speed and rotor position of a BLDC motor is presented in this paper. Fuzzy-based back-EMF observer is employed to estimate the speed by using measurements of the stator line voltage and line current. Most existing sensorless methods of the BLDC motor have low performance in a transient state or low-speed range and occasionally require an additional circuit. To overcome this problem, the estimation of back-EMF is carried out by fuzzy logic techniques to improve the performance of the system. This method proposes a back-EMF observer based on fuzzy function approximation and the system state equation of the BLDC motor and describes a fuzzy logic approach to design a Hybrid Controller (HC) for variable speeds of a BLDC motor. Here, Proportional Integral (PI) controller is tuned by the fuzzy logic technique. The fuzzy logic tuner is used to adjust the two gains of the PI controller. In this approach, the fuzzy tuning of the gains of a conventional PI controller is achieved through fuzzy rules deduced from many simulation tests applied to BLDC motor, for a variety of operating conditions. Experimental results show that the proposed fuzzy-tuning PI controller is better than the controller with fixed gains in terms of robustness and speed rise time even under great variations of operating conditions and load disturbance.

The Brushless DC (BLDC) motor has been used in many applications such as computers, automatic office machines, robots for automation of manufactory, drives of many electronics and minute machines. The BLDC motor has several advantages over the DC motor such as simple control, high torque, high efficiency and compactness. Also, brush maintenance is no longer required, and many problems resulting from the mechanical wear of brushes and commutators are eliminated by electronic commutation. To replace the function of commutators and brushes, the BLDC motor requires an inverter and a position sensor that detects the rotor position for proper commutation of current (Millar, 1989). Efforts have been made to make this motor cost-effective and reliable by avoiding the use of position sensors and employing estimators. The BLDC motor has trapezoidal electromotive force and quasi-rectangular current waveforms. Normally, sensors are used for the estimation of the speed and position of the rotor. Due to increase in the cost of the sensor and less reliability, the sensorless operation of BLDC motor has attracted wide attention in industries.

In recent years, many sensorless drive methods have been proposed for improving the performance of BLDC motors without a position sensor (Krishnan and Ghosh, 1989; Ogasawara and Akagi, 1991; Ertugrul and Acarnley, 1994; Becerra et al., 2004; and Tae-Hyung and Ehasani, 2004). However, most existing sensorless drive methods of the BLDC motor have low performance in a transient state or low-speed range and occasionally require additional circuits. To overcome this problem, the estimation of a back-EMF is carried out by fuzzy logic techniques to improve the performance of the system. This method proposes a fuzzy back-EMF observer based on fuzzy function approximation and system state equation of the BLDC motor. Here, the fuzzy logic technique can estimate the speed of the BLDC motor under variable and fixed conditions of back-EMF. Therefore, the correct back-EMF estimation senses the position and speed of the BLDC motor. This method can estimate the speed of the rotor continuously at transients as well as in the steady state even with changes in the external condition.

Recently, DC motors have been gradually replaced by BLDC motors as industrial applications require more powerful actuators in small sizes. Elimination of brushes and commutators also solves the problems associated with contacts and gives improved reliability and enhances life. The BLDC motor has low inertia, large power to volume ratio, and low noise when compared to the permanent magnet DC servo motor having the same output rating (Ohishi et al., 1987; and Pillay and Krishnan, 1991). Therefore, high-performance BLDC motor drives are widely used for variable speed drive systems of industrial applications. In the case of the control of robot arms and tracking applications with lower stiffness, we cannot design the speed controller gain with a very large value from the viewpoint of the system stability. The Proportional Integral (PI) controller is usually employed in a BLDC motor control, which is simple in realization. In this work, input to the PI control is from the fuzzy-based estimation of speed and rotor position, which is also verified with the sensor output for its correctness.

Electrical and Electronics Engineering Journal, Sensorless Brushless DC Motor, Electrical Applications, Proportional Integral Controller, Tracking Applications, Artificial Intelligent Methods, Electromagnetic Torque, Automatic Tuning Methods, Fuzzy Logic Controller, Automobile Industry, MATLAB Software, Fuzzy Logic Technique, Conventional Sensorless Methods.