Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Antenna Switch Optimizations Using Genetic Algorithms Accelerated With the Multilevel Fast Multipole Algorithm
Date
2015-07-24
Author
Onol, Can
Karaosmanoglu, Bariscan
Ergül, Özgür Salih
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
382
views
0
downloads
Cite This
We present antenna switch optimizations using an efficient mechanism based on genetic algorithms and the multi-level fast multipole algorithm (MLFMA). Genetic algorithms are used to determine switch states for desired radiation and input characteristics, while cost-function evaluations are performed efficiently via an MLFMA implementation with dynamic error control. MLFMA is integrated into the genetic algorithm by extracting common computations to be performed once per optimization. Iterative convergence rates are further accelerated by using earlier solutions as initial-guess vectors. The efficiency of the developed mechanism is demonstrated on antennas with relatively large numbers of switches.
Subject Keywords
Optimization
,
Switches
,
Genetic algorithms
,
Dipole antennas
,
MLFMA
,
Directive antennas
URI
https://hdl.handle.net/11511/46989
DOI
https://doi.org/10.1109/aps.2015.7305058
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Rigorous optimizations of three dimensional antenna arrays using full wave simulations
Onol, Can; Gokce, Ozer; Boyacı, Huseyın; Ergül, Özgür Salih (null; 2015-07-09)
We present optimizations of three-dimensional antenna arrays using heuristic techniques coupled with the multilevel fast multipole algorithm (MLFMA). Without resorting to any periodicity and infinity assumptions, antenna arrays are modeled with surface integral equations and simulated via MLFMA, which also enables the analysis of arrays with non-identical elements. Genetic algorithms and particle swarm optimization methods are employed on the complex data produced by MLFMA in phasor domain to find optimal s...
Optimizations of Patch Antenna Arrays Using Genetic Algorithms Supported by the Multilevel Fast Multipole Algorithm
Onol, Can; Ergül, Özgür Salih (2014-12-01)
We present optimizations of patch antenna arrays using genetic algorithms and highly accurate full-wave solutions of the corresponding radiation problems with the multilevel fast multipole algorithm (MLFMA). Arrays of finite extent are analyzed by using MLFMA, which accounts for all mutual couplings between array elements efficiently and accurately. Using the superposition principle, the number of solutions required for the optimization of an array is reduced to the number of array elements, without resorti...
Efficient and Accurate Electromagnetic Optimizations Based on Approximate Forms of the Multilevel Fast Multipole Algorithm
Onol, Can; Karaosmanoglu, Bariscan; Ergül, Özgür Salih (2016-01-01)
We present electromagnetic optimizations by heuristic algorithms supported by approximate forms of the multilevel fast multipole algorithm (MLFMA). Optimizations of complex structures, such as antennas, are performed by considering each trial as an electromagnetic problem that can be analyzed via MLFMA and its approximate forms. A dynamic accuracy control is utilized in order to increase the efficiency of optimizations. Specifically, in the proposed scheme, the accuracy is used as a parameter of the optimiz...
Cylindrical Microstrip Patch Array Modified Neural Multiple Source Tracking Algorithm
Caylar, Selcuk; Dural, Guelbin; Leblebicioğlu, Mehmet Kemal (2008-07-11)
In this study Cylindrical Microstrip Patch Array Modified Neural Multiple Source Tracking Algorithm (CMN-MUST) is proposed. CMN-MUST implements previously reported Modified Neural Multiple Source Tracking Algorithm (MN-MUST). CMN-MUST algorithm uses the advantage of directive pattern of microstrip patch elements by considering only a part of array elements for a chosen sector. This reduces neural network sizes and also improves the spatial filtering performance. The proposed algorithm improves MN-MUST algor...
Optimizations of antennas using heuristic algorithms supported by the multilevel fast multipole algorithm
Önol, Can; Ergül, Özgür Salih; Department of Electrical and Electronics Engineering (2015)
In this study, an optimization environment based on heuristic algorithms supported by the multilevel fast multipole algorithm (MLFMA) is presented for different antenna problems involving either excitation or geometry optimizations. The heuristic algorithms are implemented in-house by aiming more effective interactions between electromagnetic solvers and optimization algorithms, instead of black box interactions. Excitation optimizations of various array geometries for desired radiation characteristics are ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
C. Onol, B. Karaosmanoglu, and Ö. S. Ergül, “Antenna Switch Optimizations Using Genetic Algorithms Accelerated With the Multilevel Fast Multipole Algorithm,” 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46989.