Modeling and control of a brushless DC motor

Abstract

Permanent magnet brushless DC motors (PMBLDC) find wide applications in industries due to their high power density and ease of control. These motors are generally controlled using a three phase power semiconductor bridge. For starting and the providing proper commutation sequence to turn on the power devices in the inverter bridge the rotor position sensors required. Based on the rotor position, the power devices are commutated sequentially every 60 degrees. To achieve desired level of performance the motor requires suitable speed controllers. In case of permanent magnet motors, usually speed control is achieved by using proportional-integral(PI) controller. Although conventional PI controllers are widely used in the industry due to their simple control structure and ease of implementation, these controllers pose difficulties where there are some control complexity such as nonlinearity, load disturbances and parametric variations. Moreover PI controllers require precise linear mathematical models. This thesis presents a Fuzzy Logic Controller(FLC) for speed control of a BLDC by using. The Fuzzy Logic(FL) approach applied to speed control leads to an improved dynamic behavior of the motor drive system and an immune to load perturbations and parameter variations. The FLC is designed using based on a simple analogy between the control surfaces of the FLC and a given Proportional-Integral controller(PIC) for the same application. Fuzzy logic control offers an improvement in the quality of the speed response, compared to PI control. This work focuses on investigation and evaluation of the performance of a permanent magnet brushless DC motor (PMBLDC) drive, controlled by PI, and Fuzzy logic speed controllers. The Controllers are for the PMBLDC motor drive simulated using MATLAB soft ware package. Further, the PI controller has been implemented on an experimental BLDC motor set up.