|
Abstract
|
Article Information:
Optimization of PID Controller for Brushless DC Motor by using Bio-inspired Algorithms
Sanjay Kr. Singh, Nitish Katal and S.G. Modani
Corresponding Author: Sanjay Kr. Singh
Submitted: April 16, 2013
Accepted: May 21, 2013
Published: February 20, 2014 |
Abstract:
|
This study presents the use and comparison of various bio-inspired algorithms for optimizing the response of a PID controller for a Brushless DC Motor in contrast to the conventional methods of tuning. For the optimization of the PID controllers Genetic Algorithm, Multi-objective Genetic Algorithm and Simulated Annealing have been used. PID controller tuning with soft-computing algorithms comprises of obtaining the best possible outcome for the three PID parameters for improving the steady state characteristics and performance indices like overshoot percentage, rise time and settling time. For the calculation and simulation of the results the Brushless DC Motor model, Maxon EC 45 flat ф 45 mm with Hall Sensors Motor has been used. The results obtained the optimization using Genetic Algorithms, Multi-objective Genetic Algorithm and Simulated Annealing is compared with the ones derived from the Ziegler-Nichols method and the MATLAB SISO Tool. And it is observed that comparatively better results are obtained by optimization using Simulated Annealing offering better steady state response.
Key words: Brushless DC motor, controller tuning, genetic algorithm, PID controllers, PID optimization, simulated annealing , ziegler nichols
|
|
Abstract
|
PDF
|
HTML |
|
Cite this Reference:
Sanjay Kr. Singh, Nitish Katal and S.G. Modani, . Optimization of PID Controller for Brushless DC Motor by using Bio-inspired Algorithms. Research Journal of Applied Sciences, Engineering and Technology, (7): 1302-1308.
|
|
|
|
 |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
 |
| Information |
|
|
|
|
| Sales & Services |
|
|
|
|
