Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Arabian Journal for Science and Engineering
Erschienen in: Arabian Journal for Science and Engineering 3/2020

30.07.2019 | Research Article - Electrical Engineering

Runner-Root Algorithm to Control Sidelobe Level and Null Depths in Linear Antenna Arrays

verfasst von: K. R. Subhashini

Erschienen in: Arabian Journal for Science and Engineering | Ausgabe 3/2020

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Nature-inspired metaheuristic algorithms have significantly influenced the optimization problems, and there has been a great success in finding optimum solutions. The main aim of this paper is to introduce one such technique, runner-root algorithm (RRA), to the antenna community. RRA is based on the concept of plant intelligence to solve an optimization problem resembling a scenario where a plant finds the best location for its survival. The main advantage of RRA over other algorithms is the execution of exploration (global search) and exploitation (local search) phases independently with a built-in mechanism of reinitialization to overcome trapping in local minima. Hence, attempt has been made for the first time to apply this algorithm to optimize excitation current amplitudes and positions of antenna elements for linear array configurations with the objective of suppressing the sidelobe levels and/or placing nulls at prescribed locations referring to the radiation patterns. Different case studies have illustrated that RRA is capable of performing linear antenna array optimization with promising results in comparison with other well-established metaheuristic algorithms. And hence such demonstration has identified RRA as a potential candidate in the optimization domain.
Vorheriger Artikel A Novel Approach Based on Line Inequality Concept and Sine–Cosine Algorithm for Estimating Optimal Reach Setting of Quadrilateral Relays
Nächster Artikel An Alternate Method for Prediction and Analysis of Notch Characteristics in Indoor Power Lines Under Varied Channel Conditions

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Ares-Pena, F.J.; Rodriguez-Gonzalez, J.A.; Villanueva-Lopez, E.; Rengarajan, S.: Genetic algorithms in the design and optimization of antenna array patterns. IEEE Trans. Antennas Propag. 47(3), 506–510 (1999)
2.
Liao, W.-P.: Array pattern synthesis with null steering using genetic algorithms by controlling only the current amplitudes. Int. J. Electron. 86(4), 445–457 (1999)
3.
Chung, Y.C.; Haupt, R.L.: Amplitude and phase adaptive nulling with a genetic algorithm. J. Electromagn. Waves Appl. 14(5), 631–649 (2000)
4.
Karaboga, N.; Güney, K.; Akdagli, A.: Null steering of linear antenna arrays with use of modified touring ant colony optimization algorithm. Int. J. RF Microw. Comput. Aided Eng. 12(4), 375–383 (2002)
5.
Yang, S.; Gan, Y.B.; Qing, A.: Antenna-array pattern nulling using a differential evolution algorithm. Int. J. RF Microw. Comput. Aided Eng. 14(1), 57–63 (2004)
6.
Cengiz, Y.; Tokat, H.: Linear antenna array design with use of genetic, memetic and tabu search optimization algorithms. Prog. Electromagn. Res. C 1, 63–72 (2008)
7.
Dib, N.I.; Goudos, S.K.; Muhsen, H.: Application of taguchi’s optimization method and self-adaptive differential evolution to the synthesis of linear antenna arrays. Prog. Electromagn. Res. 102, 159–180 (2010)
8.
Pal, S.; Qu, B.; Das, S.; Suganthan, P.: Linear antenna array synthesis with constrained multi-objective differential evolution. Prog. Electromagn. Res. B 21, 87–111 (2010)
9.
Goudos, S.K.; Moysiadou, V.; Samaras, T.; Siakavara, K.; Sahalos, J.N.: Application of a comprehensive learning particle swarm optimizer to unequally spaced linear array synthesis with sidelobe level suppression and null control. IEEE Antennas Wirel. Propag. Lett. 9, 125–129 (2010)
10.
11.
Khodier, M.M.; Christodoulou, C.G.: Linear array geometry synthesis with minimum sidelobe level and null control using particle swarm optimization. IEEE Trans. Antennas Propag. 53(8), 2674–2679 (2005)
12.
Khodier, M.M.; Al-Aqeel, M.: Linear and circular array optimization: a study using particle swarm intelligence. Prog. Electromag. Res. B 15, 347–373 (2009)
13.
Jin, N.; Rahmat-Samii, Y.: Advances in particle swarm optimization for antenna designs: real-number, binary, single-objective and multiobjective implementations. IEEE Trans. Antennas Propag. 55(3), 556–567 (2007)
14.
Rajo-Iglesias, E.; Quevedo-Teruel, O.: Linear array synthesis using an ant-colony-optimization-based algorithm. IEEE Antennas Propag. Mag. 49(2), 70–79 (2007)
15.
Guney, K.; Basbug, S.: Interference suppression of linear antenna arrays by amplitude-only control using a bacterial foraging algorithm. Prog. Electromagn. Res. 79, 475–497 (2008)
16.
Scharf, I.; Subach, A.; Ovadia, O.: Foraging behaviour and habitat selection in pit-building antlion larvae in constant light or dark conditions. Anim. Behav. 76(6), 2049–2057 (2008)
17.
Sharaqa, A.; Dib, N.: Circular antenna array synthesis using firefly algorithm. Int. J. RF Microw. Comput. Aided Eng. 24(2), 139–146 (2014)
18.
19.
Singh, U.; Rattan, M.: Design of linear and circular antenna arrays using cuckoo optimization algorithm. Prog. Electromagn. Res. C 46, 1–11 (2014)
20.
Guney, K.; Onay, M.: Optimal synthesis of linear antenna arrays using a harmony search algorithm. Expert Syst. Appl. 38(12), 15 455–15 462 (2011)
21.
Roy, G.G.; Das, S.; Chakraborty, P.; Suganthan, P.N.: Design of non-uniform circular antenna arrays using a modified invasive weed optimization algorithm. IEEE Trans. Antennas Propag. 59(1), 110–118 (2011)
22.
Pappula, L.; Ghosh, D.: Constraint-based synthesis of linear antenna array using modified invasive weed optimization. Prog. Electromagn. Res. M 36, 9–22 (2014)
23.
Pappula, L.; Ghosh, D.: Large array synthesis using invasive weed optimization. In: International Conference on Microwave and Photonics (ICMAP), pp. 1–6. IEEE (2013)
24.
Guney, K.; Durmus, A.; Basbug, S.: A plant growth simulation algorithm for pattern nulling of linear antenna arrays by amplitude control. Prog. Electromagn. Res. B 17, 69–84 (2009)
25.
Karimkashi, S.; Kishk, A.A.: Invasive weed optimization and its features in electromagnetics. IEEE Trans. Antennas Propag. 58(4), 1269–1278 (2010)
26.
Zaharis, Z.D.; Lazaridis, P.I.; Cosmas, J.; Skeberis, C.; Xenos, T.D.: Synthesis of a near-optimal high-gain antenna array with main lobe tilting and null filling using taguchi initialized invasive weed optimization. IEEE Trans. Broadcast. 60(1), 120–127 (2014)
27.
El-Fergany, A.: Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm. Int. J. Electric. Power Energy Syst. 64, 1197–1205 (2015)
28.
Civicioglu, P.: Circular antenna array design by using evolutionary search algorithms. Prog. Electromagn. Res. B 54, 265–284 (2013)
29.
Civicioglu, P.: Backtracking search optimization algorithm for numerical optimization problems. Appl. Math. Comput. 219(15), 8121–8144 (2013)MathSciNetMATH
30.
Askarzadeh, A.; dos Santos Coelho, L.: A backtracking search algorithm combined with burger’s chaotic map for parameter estimation of pemfc electrochemical model. Int. J. Hydrog. Energy 39(21), 11165–11174 (2014)
31.
32.
Merzougui, A.; Bonilla-Petriciolet, A.; Hasseine, A.; Laiadi, D.; Labed, N.: Modeling of liquid–liquid equilibrium of systems relevant for biodiesel production using backtracking search optimization. Fluid Phase Equilib. 388, 84–92 (2015)
33.
Saxena, P.; Kothari, A.: Linear antenna array optimization using flower pollination algorithm. SpringerPlus 5(1), 1 (2016)
34.
Babayigit, B.; Ozdemir, R.: Design of non-uniform circular antenna using a modified ABC algorithm. In: Electrical, Electronic and Computer Engineering Symposium, Bursa, Turkey, pp. 238–241 (2012)
35.
Li, X.; Yang, G.: Artificial bee colony algorithm with memory. Appl. Soft Comput. 41, 362–372 (2016)
36.
Guney, K.; Onay, M.: Amplitude-only pattern nulling of linear antenna arrays with the use of bees algorithm. Prog. Electromagn. Res. 70, 21–36 (2007)
37.
38.
Pappula, L.; Ghosh, D.: Linear antenna array synthesis using cat swarm optimization. AEU Int. J. Electron. Commun. 68(6), 540–549 (2014)
39.
Mirjalili, S.; Mirjalili, S.M.; Hatamlou, A.: Multi-verse optimizer: a nature-inspired algorithm for global optimization. Neural Comput. Appl. 27(2), 495–513 (2016)
40.
Talatahari, S.: Optimum design of skeletal structures using ant lion optimizer. Iran Univ. Sci. Technol. 6(1), 13–25 (2016)
41.
42.
Saxena, P.; Kothari, A.: Ant lion optimization algorithm to control side lobe level and null depths in linear antenna arrays. AEU Int. J. Electron. Commun. 70(9), 1339–1349 (2016)
43.
44.
Singh, U.; Kumar, H.; Kamal, T.S.: Linear array synthesis using biogeography based optimization. Prog. Electromagn. Res. 11, 25–36 (2010)
45.
Singh, U.; Kamal, T.: Design of non-uniform circular antenna arrays using biogeography-based optimisation. IET Microw. Antennas Propag. 5(11), 1365–1370 (2011)
46.
Weng, W.-C.; Choi, C.T.: Optimal design of cpw slot antennas using Taguchi’s method. IEEE Trans. Magn. 45(3), 1542–1545 (2009)
47.
Agastra, E.; Pelosi, G.; Selleri, S.; Taddei, R.: Taguchi’s method for multi-objective optimization problems. Int. J. RF Microw. Comput. Aided Eng. 23(3), 357–366 (2013)
48.
49.
Hesari, M.; Ebrahimzadeh, A.: Introducing deeper nulls and reduction of side-lobe level in linear and non-uniform planar antenna arrays using gravitational search algorithm. Prog. Electromagn. Res. 73, 131–145 (2017)
50.
51.
52.
Singh, U.; Salgotra, R.: Synthesis of linear antenna array using flower pollination algorithm. Neural Comput. Appl. 29(2), 435–445 (2018)
53.
Rahman, S.U.; CAO, Q.; Ahmed, M.M.; Khalil, H.: Analysis of linear antenna array for minimum side lobe level, half power beamwidth, and nulls control using pso. J. Microw. Optoelectron. Electromagn. Appl. 16(2), 577–591 (2017)
54.
Jaspreet Kaur, D.S.G.: Optimal side lobes reduction of linear array antenna using crow search algorithm. Int. J. Res. Appl. Sci. Eng. Technol. 5, 7–8 (2017)
55.
Merrikh-Bayat, F.: The runner-root algorithm: a metaheuristic for solving unimodal and multimodal optimization problems inspired by runners and roots of plants in nature. Appl. Soft Comput. 33, 292–303 (2015)
56.
Balanis, C.A.: Antenna Theory: Analysis and Design. Wiley, New York (2012)
57.
Nguyen, T.T.; Nguyen, T.T.; Truong, A.V.; Nguyen, Q.T.; Phung, T.A.: Multi-objective electric distribution network reconfiguration solution using runner-root algorithm. Appl. Soft Comput. 52, 93–108 (2017)
58.
Cebrian, J.C.; Kagan, N.: Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms. Electr. Power Syst. Res. 80(1), 53–62 (2010)
59.
Nguyen, T.T.; Truong, A.V.; Phung, T.A.: A novel method based on adaptive cuckoo search for optimal network reconfiguration and distributed generation allocation in distribution network. Int. J. Electric. Power Energy Syst. 78, 801–815 (2016)
60.
Ibrahim, R.A.; Oliva, D.; Ewees, A. A.; Lu, S.: Feature selection based on improved runner-root algorithm using chaotic singer map and opposition-based learning. In: International Conference on Neural Information Processing. Springer, pp. 156–166 (2017)
61.
Shi, Y.; Eberhart, R.C.: Empirical study of particle swarm optimization. In: Proceedings of the 1999 Congress on Evolutionary Computation. CEC 99, vol. 3, pp. 1945–1950. IEEE (1999)
62.
Mahdavi, M.; Fesanghary, M.; Damangir, E.: An improved harmony search algorithm for solving optimization problems. Appl. Math. Comput. 188(2), 1567–1579 (2007)MathSciNetMATH
63.
64.
Merad, L.; Bendimerad, F.; Meriah, S.: Design of linear antenna arrays for side lobe reduction using the tabu search method. Int. Arab. J. Inf. Technol. 5(3), 219–222 (2008)
Metadaten
Titel
Runner-Root Algorithm to Control Sidelobe Level and Null Depths in Linear Antenna Arrays
verfasst von
K. R. Subhashini
Publikationsdatum
30.07.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Arabian Journal for Science and Engineering / Ausgabe 3/2020
Print ISSN: 2193-567X
Elektronische ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-019-04051-x

Weitere Artikel der Ausgabe 3/2020

Arabian Journal for Science and Engineering 3/2020 Zur Ausgabe

Research Article-Electrical Engineering

Adaptive Control of a Two-Link Flexible Manipulator Using a Type-2 Neural Fuzzy System

Research Article - Systems Engineering

Dynamic Control of a Machine Repair Problem with Switching Failure and Unreliable Repairmen

Research Article - Systems Engineering

Modified Whale Optimization Algorithm for Infinitive Impulse Response System Identification

Research Article - Systems Engineering

Power Geometric Aggregation Operators Based on Connection Number of Set Pair Analysis Under Intuitionistic Fuzzy Environment

Research Article - Electrical Engineering

Reconfiguration of Distribution Network for Transformer Life Extension Using Quasi-static Time-Series Analysis

Research Article - Electrical Engineering

Hybrid Turbo Coding PTS with Enhanced Switching Algorithm Employing DE to Carry Out Reduction in PAPR in AUL-Based MIMO-OFDM

Premium Partner

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen. 

    Zur Marktübersicht
    Bildnachweise