Nature Inspired Optimization Algorithms to BLDC Motor Drive - Merugumalla, M. K.
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The brushless direct current (BLDC) motor is being used in Aerospace, Naval, Military, automation and household appliances due to its advantages such as High efficiency, noiseless operation and wide speed range. The BLDC motor is innately electronic controlled and requires rotor position information for correct commutations of current. The issues with rotor position sensors have motivated research in the demesne of sensorless motor drives. Sensorless control has been an active research motive for the last three decades. The Bio-inspired optimization algorithms such as particle swarm…mehr

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Produktbeschreibung
The brushless direct current (BLDC) motor is being used in Aerospace, Naval, Military, automation and household appliances due to its advantages such as High efficiency, noiseless operation and wide speed range. The BLDC motor is innately electronic controlled and requires rotor position information for correct commutations of current. The issues with rotor position sensors have motivated research in the demesne of sensorless motor drives. Sensorless control has been an active research motive for the last three decades. The Bio-inspired optimization algorithms such as particle swarm optimization algorithm with several inertia weight strategies(SPSO, CIPSO, and CPSO), Bat algorithm (BA) and Firefly algorithm (FFA)were developed to tune PID controller parameters for the speed control of BLDC motor.
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Autorenporträt
Dr. Manoj Kumar Merugumalla is currently working as an Associate professor & Head in the department of EEE, Tirumala Engineering College, Jonnalagadda, Guntur, A.P. He was awarded Ph.D. from Andhra University, Visakhapatnam. His current research interests focus on the Control of Electric motor drives and renewable energy sources.