DocumentCode :
720727
Title :
Performance analysis of swimming microrobot using GA, ABC and PSO based-optimization techniques
Author :
Meguellati, M. ; Srairi, F. ; Djeffal, F. ; Saidi, L.
Author_Institution :
Dept. of Electron., Univ. of Batna, Batna, Algeria
fYear :
2015
fDate :
28-30 April 2015
Firstpage :
310
Lastpage :
314
Abstract :
Further progress in the development, innovation and optimization of microrobot-based applications leads to the requirement of new modeling tools and hypothesis, for enhancing the performance and the computational time of microrobots simulators. In this context, the aim of this work is to compare the accuracy and computational efficiency of ABC, GA and PSO evolutionary techniques for optimizing and improving the performance of the microrobot devices. Besides, our obtained results for all techniques (PSO, GA and ABC) are presented and compared using our optimization techniques, in order to demonstrate the accuracy of each technique. In this context, a good improvement of the electromechanical performance has been founded for all optimization-based techniques.
Keywords :
computational complexity; genetic algorithms; microrobots; mobile robots; particle swarm optimisation; ABC based-optimization technique; GA based-optimization technique; PSO based-optimization technique; computational efficiency; computational time; electromechanical performance; evolutionary technique; microrobot device; microrobot-based application; microrobots simulator; performance analysis; swimming microrobot; Computational modeling; Force; Genetic algorithms; Optimization; Performance evaluation; Sociology; Statistics; Genetic Algorithm (GA); Particle Swarm Optimization (PSO); Thrust force; artificial bee colony (ABC); swimming microrobot;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Control (ICSC), 2015 4th International Conference on
Conference_Location :
Sousse
Print_ISBN :
978-1-4673-7108-7
Type :
conf
DOI :
10.1109/ICoSC.2015.7153277
Filename :
7153277
Link To Document :
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