Genetic Algorithm: An approach to Velocity Control of an Electric DC Motor

Anandaraju, M. B.; Puttaswamy, P. S.; Rajpurohit, Jaswant Singh

doi:10.5120/3066-4191

Cited by 9 publications

(5 citation statements)

References 10 publications

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“…Different error models used in [8] are considered for optimization and the PID controller parameters are evaluated.…”

Section: Discussionmentioning

confidence: 99%

“…Speed control of electric DC motor using GA was demonstrated in [8]. A comparative study of optimization using modified IEC and GA has been carried out in the present work.…”

Section: Comparative Study With Genetic Algorithmmentioning

confidence: 99%

“…A comparative study of optimization using modified IEC and GA has been carried out in the present work. The modified IEC targeted to achieve the fitness function values achieved in [8] in lesser number of generations.…”

Section: Comparative Study With Genetic Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

Modified Interactive Evolutionary Computing for Speed Control of an Electric DC Motor

Anandaraju¹,

Puttaswamy²

2012

IJCA

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DC motors are important components of most of the process control industries. PID controllers are extensively used in DC motors for speed as well as position control. Tuning of PID controller parameters is an iterative process and needs an optimization to achieve the desired performance. In this paper a modified form of Interactive Evolutionary Computing (IEC) is used as the tool for achieving optimization of PID controller parameters for the speed control of DC motor. Different error models are used for optimization and a comparison with Genetic Algorithm based approach is presented.

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“…Different error models used in [8] are considered for optimization and the PID controller parameters are evaluated.…”

Section: Discussionmentioning

confidence: 99%

“…Speed control of electric DC motor using GA was demonstrated in [8]. A comparative study of optimization using modified IEC and GA has been carried out in the present work.…”

Section: Comparative Study With Genetic Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Modified Interactive Evolutionary Computing for Speed Control of an Electric DC Motor

Anandaraju¹,

Puttaswamy²

2012

IJCA

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“…2. The closed-loop of the HSFESS for PID parameter calculation In reference [28], some error criteria used in the calculation of the optimum values of the PID parameters are given. For a PID-controlled system, there are often four indices depicting the system performance: IAE, ISE, ITAE and ITSE.…”

Section: Ziegler-nichols Methods and Ga/ps Optimizationmentioning

confidence: 99%

A Method for Current Control of the Flywheel Energy Storage System Used in Satellites

Çelikel

Özdemir

2019

Teh. vjesn.

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Satellites have a dark region and a bright region in their orbit path. The flywheel energy storage unit is an electric energy provider for a satellite in the dark region. Brushless dc motors (BLDC) are used in the flywheel energy storage unit. The current surge of the BLDC motors is an undesirable situation for solar panels which are used in the satellite motion systems and satellite power systems. Therefore, the current reference method (CRM) is preferred in these systems. The setting of the controller parameters (proportional (P), integral (I) and derivative (D)) is an important problem for the control of the BLDC motor current. Optimum performance cannot be obtained by the calculation of PID parameters using conventional methods. In recent years, hybrid genetic algorithms (GA) are used in the solution of complex problems. In this study, a CRM method was proposed to protect the satellite power system and solar panels. The defined block diagram for the CRM method was used to control the current of the BLDC. In order to calculate conventional method and hybrid GA-based method, the performance of the PID controllers was compared by using MATLAB/SimPowerSystem blocks.

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“…Researchers have incorporated intelligence using techniques like neural networks [6] [7], genetic algorithms [8] [17],evolutionary computing [9] and fuzzy logic [10] [14]. The use neuro-fuzzy techniques for control is also gaining popularity [11] [12] [13] [15].…”

Section: Introductionmentioning

confidence: 99%

Multi-layer Neural Network for Servo Motor Control

A¹,

Puttaswamy²,

Dhruve³

2013

IJCA

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AC servo systems are extensively used in robotic actuators and are competing with DC servo motors for motion control because of their favorable electrical and mechanical properties. This paper presents an approach towards the control system tuning for the speed control of an AC servo motor. An approach towards speed control of servo motor in presence of system parameter variations is presented. Multi-layer Artificial Neural Networks are designed and trained to model the plant parameter variations. Improvements in the speed control performance are presented for smaller variations and larger variations in the motor parameters and the load conditions.

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Genetic Algorithm: An approach to Velocity Control of an Electric DC Motor

Cited by 9 publications

References 10 publications

Modified Interactive Evolutionary Computing for Speed Control of an Electric DC Motor

Modified Interactive Evolutionary Computing for Speed Control of an Electric DC Motor

A Method for Current Control of the Flywheel Energy Storage System Used in Satellites

Multi-layer Neural Network for Servo Motor Control

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