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Implementation of Nature-Inspired Optimization Algorithms for BLDC Motor Drive Control

Manoj Kumar Merugumalla*

Department of Electrical and Electronics Engineering, Tirumala Engineering College, Jonnalagadda, Andhra Pradesh, India.

Periodicity:February - April'2019
DOI : https://doi.org/10.26634/jic.7.2.16717

Abstract

Nature-inspired optimization algorithms are presented in this paper for the control of brushless direct current (BLDC) motor drive. These algorithms have a number of advantages over classical methods for solving complex optimization problems. The algorithms in this class are based on perceptive behaviour of well ordered members of the population. This type of nature can be found among birds, fishes and insects, such as ants, bees, and the like. These algorithms have mastery over classical methods for solving complex and badly corroborated problems. The key feature of the population algorithms is that the search strategy should be simple and independent. No agent should have dominance over the entire search process. The commutation is implemented electronically in this motor drive using power electronic switches to modify current in the windings based on rotor position. The BLDC motor is just a reversed DC commutator motor, as its conductors remain stationary while magnet rotates facilitating the internal or external position sensors in the motors to sense the actual position of rotor. The rotor position can also be found by the measurement of variations in the Back emf, which is known as sensorless control method. This method reduces the cost as well as the size of the motor as it does not require sensors for determining rotor position. Matlab/simulink is used for modelling drive system. The simulation results with the proposed optimization algorithms are effective in controlling the speed of the drive system.

Keywords

Brushless Direct Current Motor (BLDC), Particle Swarm Optimization (PSO), Bat Algorithm (BA), Position, Velocity, PID Controller, Objective Function.

How to Cite this Article?

Merugumalla, M. K. (2019). Implementation of Nature-Inspired Optimization Algorithms for BLDC Motor Drive Control. i-manager's Journal on Instrumentation and Control Engineering, 7(2), 32-41. https://doi.org/10.26634/jic.7.2.16717

References

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Implementation of Nature-Inspired Optimization Algorithms for BLDC Motor Drive Control

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