A novel strategy using H infinity theory with optimum weight selection for the robust control of sensorless brushless DC motor

Vinida, K.; Chacko, Mariamma

doi:10.1109/sled.2016.7518799

Cited by 10 publications

(2 citation statements)

References 6 publications

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“…The authors observed that good tracking of speed and rejection of disturbances have been achieved in simulation with the coefficients of weights optimized using particle swarm optimization (PSO) algorithm for proposed controller [23]. A simulation has been carried out to study the four quadrant operation of the motor and also the proposed speed controller has been compared with PI controller and the performance parameters are analyzed [24], [25].…”

Section: Introductionmentioning

confidence: 99%

Implementation of speed control of sensorless brushless DC motor drive using H-infinity controller with optimized weight filters

Vinida

Chacko

2021

IJPEDS

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<span>The hardware implementation of sensorless brushless direct current motor drive incorporating H-infinity control strategy with optimized weights by particle swarm optimization in the speed control is carried out in this work. The methodology involved in the design of brushless direct current (BLDC) motor control with sensorless position detection technique, the design of H-infinity speed controller, steps involved in particle swarm optimization for optimizing coefficients of its weights and the hardware implementation is discussed in detail in this paper. Texas Instruments microcontroller board C2000 Delfino Launchpad LAUNCHXL F28377S and driver BOOSTXL DRV8301 are used for realization of the speed controller. The code is developed using C2000 hardware support package in MATLAB/SIMULINK platform. A comprehensive performance analysis is accomplished during starting of the motor and during the fast application and removal of load. This strategy is found to be robust resulting in faster load disturbance rejection and better reference speed tracking. The experimental results of the proposed strategy are compared with that of conventional proportional-integral (PI) controller. The time domain parameters are also compared. It is found that the proposed strategy exhibits better performance characteristics during transients and sudden disturbances in load.</span>

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Section: Introductionmentioning

confidence: 99%

Implementation of speed control of sensorless brushless DC motor drive using H-infinity controller with optimized weight filters

Vinida

Chacko

2021

IJPEDS

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“…Particle swarm optimization (PSO) and Genetic Algorithm (GA) approach have been compared to find out the efficient one [25][26][27][28]. In order to attain robust control for BLDC motor exclusively in the presence of external disturbances such as ocean currents and wave drifts, H infinity controller with PSO optimised weights has been proposed by this author in the speed control loop and the simulation results have been discussed in detail [29][30].…”

Section: Introductionmentioning

confidence: 99%

An Optimized Speed Controller for Electrical Thrusters in an Autonomous Underwater Vehicle

Vinida

Chacko

2018

IJPEDS

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<span lang="EN-US">This paper focuses on the development of a prototype of thruster motor speed controller which exhibits robust performance for an Autonomous underwater vehicle. H infinity based speed controller with particle swarm optimized weights for a sensorless BLDC motor which is used as electrical thruster has been simulated in MATLAB/ SIMULINK and implemented using TI C2000 Delfino LaunchPad LaunchXL-F28377S and BoostXL DRV 8301. A performance comparison in reference tracking has been done with conventional PI controller and experimental results have been discussed in detail. The percentage variation in speed with respect to reference speed of proposed strategy has been observed to be 0.65% whereas it is 1.1% with PI controller. It has also been found that the proposed control strategy exhibits smooth starting with better reference tracking and less torque ripples.</span>

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Control System Design for Cogging Torque Reduction Based on Sensor-Less Architecture

Dini

Saponara

2020

Lecture Notes in Electrical Engineering

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A novel strategy using H infinity theory with optimum weight selection for the robust control of sensorless brushless DC motor

Cited by 10 publications

References 6 publications

Implementation of speed control of sensorless brushless DC motor drive using H-infinity controller with optimized weight filters

Implementation of speed control of sensorless brushless DC motor drive using H-infinity controller with optimized weight filters

An Optimized Speed Controller for Electrical Thrusters in an Autonomous Underwater Vehicle

Control System Design for Cogging Torque Reduction Based on Sensor-Less Architecture

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