Abstract
Jason Lohn and his workmates in NASA Ames Research Center have evolved an X-band antenna for NASA’s Space Technology 5 (ST5) mission which is the first evolved hardware in space. However their approach did not put too much attention on the efficiency of the evolutionary algorithm. Owing to the flaw we employ GT Algorithm to tackle constraints and balance multi-objective via normalization which makes evolution more efficient. Moreover we adopt a kind of linear real-values code to describe the structure of antenna so that it is easier to carry out genetic operations and control the size of the antenna. We have evolved a wire antenna successfully via this approach and all the targets have been meted.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Michielssen, E., Sajer, J.-M., Ranjithan, S., Mittra, R.: Design of lightweight, broad-band microwave absorbers using genetic algorithms. IEEE Transactions on Microwave Theory and Techniques 41(6), 1024–1031 (1993)
Haupt, R.L.: An introduction to genetic algorithms for electromagnetics. Antennas and Propagation Magazine, IEEE 37(2), 7–15 (1995)
Linden, D.S., Altshuler, E.E.: Automating Wire Antenna Design using Genetic Algorithms. Microwave Journal 39(3) (March 1996)
Linden, D.S., Altshuler, E.E.: Evolving Wire Antennas Using Genetic Algorithms: A Review. In: Proceedings of the First NASA/DoD Workshop on Evolvable Hardware, pp. 225–232 (1999)
Globus, A., Linden, D., Lohn, J.: Evolutionary Design of a Phased Array Antenna Element. In: Antennas and Propagation Society International Symposium 2006, July 9-14, pp. 2071–2074. IEEE, Los Alamitos (2006)
Lohn, J.D., Kraus, W.F., Linden, D.S.: Evolutionary optimization of a quadrifilar helical antenna. In: Antennas and Propagation Society International Symposium, vol. 3, pp. 814–817. IEEE, Los Alamitos (2002)
Linden, D.S.: In-situ evolution of a reconfigurable antenna. In: IEEE Proceedings of Aerospace Conference, vol. 5, pp. 2333–2338 (2001)
Space Technology 5 Mission, http://nmp.jpl.nasa.gov/st5/
Deb, K.: An efficient constraint handling method for genetic algorithms. Computer Methods in Applied Mechanics and Engineering 186(2-4), 311–338 (2000)
Takahama, T., Sakai, S.: Constrained Optimization by the ε Constrained Differential Evolution with Gradient-Based Mutation and Feasible Elites. In: IEEE Congress on Evolutionary Computation, CEC 2006, July 16-21, pp. 1–8 (2006)
Liang, J.J., Runarsson, T.P., Mezura-Montes, E., Clerc, M., Suganthan, P.N., Coello, C.A.C., Deb, K.: Problem definitions and evaluation criteria for the CEC2006 special session on constrained real-parameter optimization (2006)
Guo, T., Kang, L.: A new evolutionary algorithm for function optimization. Wuhan University Journal of Natural Sciences 4(4) (1999)
Lohn, J.D., Linden, D.S., Hornby, G.S., Rodriguez-Arroyo, A., Seufert, S.E., Blevins, B., Greenling, T.: Evolutionary Design of a Single-Wire Circularly-polarized X-Band Antenna. In: Antennas and Propagation Society International Symposium, vol. 2B, pp. 267–270. IEEE, Los Alamitos (2005)
Numerical Electromagnetics Code NEC2 unofficial home page, http://www.nec2.org/
NEC-2 Manual, Part III: User’s Guide, http://www.nec2.org/other/nec2prt3.pdf
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fan, Y., Liang, Q., Cai, Z., Li, H. (2008). Evolutionary Antenna Design via Modified Normalized GT Algorithm. In: Kang, L., Cai, Z., Yan, X., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2008. Lecture Notes in Computer Science, vol 5370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92137-0_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-92137-0_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92136-3
Online ISBN: 978-3-540-92137-0
eBook Packages: Computer ScienceComputer Science (R0)