A Metaheuristic Optimization Algorithm-Based Speed Controller for Brushless DC Motor: Industrial Case Study

Abstract

190In this chapter, a metaheuristic optimization algorithm-based variable speed control (VSC) of brushless DC (BLDC) motor with excellent time-domain performance index is presented as an industrial case study. It is required for energy saving in a large number of modern industries (Industry 4.0), home appliances, medical instruments, defence, etc. The electric motor efficiency can be increased from 15% to 30% and reduced electric energy utilization cost by the presence of metaheuristic optimization algorithm-based VSC drives. Hence, this industrial case study deals with optimization technique-based optimal tuning of controllers such as proportional integral derivative (PID) and fractional order PID (FOPID) controllers for VSC drives. FOPID controller has five control parameters (, , , λ and μ) that need to be tuned for getting optimal values, which makes the tuning rules more difficult. Hence, metaheuristic optimization algorithms are used for generating the optimal controller parameters to achieve the robust performance of the system by minimizing the significant parameters such as rise time, peak time, settling time, steady-state error, control efforts and performance indices. Here, various metaheuristic optimization algorithms are reviewed for tuning PID/FOPID controllers for sensorless speed control of BLDC motor drives. The various controllers for the sensorless speed control of BLDC motor are evaluated under different operating conditions: (i) constant load conditions, (ii) varying load conditions, (iii) changing set speed conditions, and (iv) a combination of (ii) and (iii) simultaneously. Based on the time-domain characteristic, the best controller is selected and proposed for improving the robust control design characteristics, which is suitable for Industry 4.0.