Studies on performance improvement Of sensorless speed control of bldc Motors using fractional order pid Controller

Abstract

This thesis presents intelligent techniques based Fractional Order Proportional Integral Derivative (FOPID) controller for sensorless speed control of Brushless Direct Current (BLDC) motors using Modified Genetic Algorithm (MGA), Artificial Bee Colony (ABC) and Bat Algorithm (BA). Permanent magnet BLDC motors play a vital role in modern engineering applications. BLDC motor drives are consistently used for obtaining high efficiency and good controllability. Its applications are in home appliances, medical equipment, industrial automation, robotics and aerospace, etc. A BLDC motor can obtain the required commutation process with the help of an inverter and a rotor position sensor such as Hall Effect sensor or variable reluctance sensor. Hence a BLDC motor need not have brushes and mechanical commutator. However, a Hall Effect position sensor has more drawbacks due to the failure of its components and electrical noise aspects.Many researchers have described sensorless commutation processes for robust controlling of the speed of BLDC motor drives. The sensorless BLDC motor drive produces effective speed and position control without a shaft mounted position sensor in a closed loop feedback system. Further a FOPID controller gives better speed control and time domain characteristics in the sensorless speed control of the BLDC motor. The FOPID controller is an extension of the Integer Order Proportional Integral Derivative (IOPID) controller. The FOPID controller is based on fractional order calculus which was developed by Igor Podlubny (1994). A typical FOPID controller consists of five degrees of freedom newline