Using the particle swarm optimizer to solve for PID values for a BLDC motor

The PSO is a new optimizing algorithm developed in the mid 1990's. Its potential to find optimized PID values for a BLDC motor is investigated in this thesis. A transfer function is developed to model a BLDC motor and the associated components. PID values that are used in the model come form the real systems' tool for finding optimized PID values. This model is then analyzed by using the root locus method. Based upon the optimized values from the real system a range of minimum and maximum values is selected. From the range of values, the PSO is performed to find optimized PID values. The PSO PID values are then inserted into the same model used to test for the real systems PID values. A root locus analysis is performed and the performance characteristics of the PSO PID values are compared with the performance characteristics from the real system. The PID values for both the PSO and the real system are then implemented in the real system for a real time performance analysis.