TY - GEN
T1 - Optimization of power electronic circuits using ant colony system
AU - Zhang, Jun
AU - Chung, Henry S. H.
AU - Lo, Alan W. L.
AU - Huang, Tao
PY - 2008
Y1 - 2008
N2 - Ant colony optimization (ACO) is typically used to search paths through graphs. The concept is based on simulating the behavior of ants in finding paths from the colony to food. Its searching mechanism is applicable for optimizing electric circuits with components, like resistors and capacitors, available in discrete values. In this paper, an extended ACO (eACO) that can search the optimal values of components manufactured in discrete and continuous values is presented. The idea is based on using the orthogonal design method (ODM) to dynamically update the database of the continuous components so that those components will have pseudo-discrete values in the search space. To speed up the optimization process, the ODM performs local search of the best combination around the best ant. The eACO also takes the component tolerances into account in evaluating the fitness value of each ant. The proposed algorithm has been successfully used to optimize the design of a buck regulator. The predicted results have been compared with the published results available in the literature and have also verified with experimental measurements. ©2008 IEEE.
AB - Ant colony optimization (ACO) is typically used to search paths through graphs. The concept is based on simulating the behavior of ants in finding paths from the colony to food. Its searching mechanism is applicable for optimizing electric circuits with components, like resistors and capacitors, available in discrete values. In this paper, an extended ACO (eACO) that can search the optimal values of components manufactured in discrete and continuous values is presented. The idea is based on using the orthogonal design method (ODM) to dynamically update the database of the continuous components so that those components will have pseudo-discrete values in the search space. To speed up the optimization process, the ODM performs local search of the best combination around the best ant. The eACO also takes the component tolerances into account in evaluating the fitness value of each ant. The proposed algorithm has been successfully used to optimize the design of a buck regulator. The predicted results have been compared with the published results available in the literature and have also verified with experimental measurements. ©2008 IEEE.
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U2 - 10.1109/PESC.2008.4592300
DO - 10.1109/PESC.2008.4592300
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781424416684
SP - 2396
EP - 2402
BT - PESC Record - IEEE Annual Power Electronics Specialists Conference
T2 - 39th IEEE Annual Power Electronics Specialists Conference (PESC '08)
Y2 - 15 June 2008 through 19 June 2008
ER -