طراحی آنتن تک قطبی مسطح بهینه شده با استفاده از الگوریتم بهینه‌سازی چند منظوره ترکیبی و توابع آشوب‌ناک
وحید حسینی
1
(
گروه مهندسی کامپیوتر، واحد ارومیه، دانشگاه آزاد اسلامی، ارومیه، ایران-گروه مهندسی کامپیوتر و فناوری اطلاعات، دانشگاه پیام نور، تهران، ایران
)
یوسف فرهنگ
2
(
گروه مهندسی کامپیوتر، واحد ارومیه، دانشگاه آزاد اسلامی، ارومیه، ایران
)
کامبیز مجید زاده
3
(
گروه مهندسی کامپیوتر، واحد ارومیه، دانشگاه آزاد اسلامی، ارومیه، ایران
)
چنگیز قبادی
4
(
گروه مهندسی الکترونیک، دانشگاه ارومیه، ارومیه، ایران
)
کلید واژه: الگوریتم ازدحام ذرات و الگوریتم ژنتیک, تابع آشوب‌ناک, آنتن تک قطبی, : الگوریتم بهینه‌سازی,
چکیده مقاله :
این تحقیق از یک الگوریتم بهینه‌سازی چند هدفه جدید برای طراحی یک آنتن یک قطبی با ویژگی‌های الکترومغناطیسی خاص استفاده می‌کند. این الگوریتم از یک تابع آشوب‌ناک ترکیبی برای ادغام الگوریتم ازدحام ذرات جهش‌یافته سفارشی شده با الگوریتم ژنتیک اصلاح‌شده استفاده می‌نماید. رویکرد جدید با اجتناب از به دام افتادن در حداقل‌های محلی، سریع‌تر از الگوریتم‌های متداول ازدحام ذرات و الگوریتم ژنتیک به نتایج دلخواه نیل می‌نماید. عملکرد الگوریتم فرا ابتکاری پیشنهادی با استفاده از توابع معیار مانند تابع راستریگن، تابع آکلی، تابع روزنبروک و تابع بووث با موفقیت شبیه‌سازی و تثبیت شده‌اند. در نهایت، اعتبار رویکرد ارائه شده برای کاربردهای الکترومغناطیسی با بهینه‌سازی یک آنتن تک قطبی مایکرواستریپ مسطح با ساختاری ساده نشان داده می‌شود، به طوری که S_11 بهینه شده آن کمتر از 10- دسی‌بل در باند فرکانسی 3/3 تا 8/3 گیگاهرتز و کمتر از 40- دسی‌بل در فرکانس رزونانس 5/3 گیگاهرتز با کاربردهای مخابرات نسل 5 باشد. الگوریتم اجازه می‌دهد تا معیارهای بهینه‌سازی طوری سفارشی شوند که به نتایج از پیش تعریف شده برای افت بازگشتی و فرکانس رزونانس میل نمایند. الگوریتم بهینه‌سازی توسعه یافته در متلب، برای تعیین تنظیمات پارامترهای لازم به منظور دستیابی به باندهای فرکانسی مورد انتظار با استفاده از الگوریتم ازدحام ذرات جهش‌یافته سفارشی یا ژنتیک اصلاح شده ابتکاری استفاده شود. در حالی که شبیه‌سازهای فرکانس بالا و الکترومغناطیسی با استفاده از برنامه شبیه‌ساز سی اس تی انجام می‌شود. ابعاد عناصر آنتن پیشنهادی، پارامترهای ورودی حیاتی الگوریتم هستند که به طور قابل توجهی بر عملکرد آنتن تأثیر می‌گذارند.
چکیده انگلیسی :
This study uses a novel multi-objective optimization algorithm for designing a planar microstrip monopole antenna that meets specialized electromagnetic requirements. The algorithm incorporates a Modified Genetic Algorithm (MGA) with a Customized Mutated PSO (CM-PSO) algorithm, utilizing a hybrid chaotic function to evade trapping local minima and achieve anticipated results more rapidly than clasical PSO and GAs. The proposed metaheuristic algorithm has been successfully simulated and stabilized using Benchmark Functions (BFs) including Booth's function (BF), Rosenbrook's function (RoF), Ackley's function (AF), and Rastrigen's function (RaF) and its validity for electromagnetic applications is demonstrated by optimizing a planar microstrip monopole antenna. The algorithm allows customization of optimization criteria to achieve predetermined results for S_11 and resonance frequency. Indeed, S_11 is set to be less than -10 dB in the frequency band of 3.3 to 3.8 GHz and -40 dB at the resonant frequency of 3.5 GHz with 5th generation telecommunication applications. In this research, MATLAB used to determine necessary parameter settings and the CST simulator software employed for high frequency and electromagnetic simulations. The dimensions of the antenna elements significantly impact the antenna's performance and are critical input parameters for the algorithm.
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[2] S. Jin, H. Lee and J. Jeong, "Fast partial distortion elimination algorithm based on hadamard probability model," Electronics Letters, vol. 44, no. 1, pp. 11-17, doi: 10.1049/el:20082872.
[3] Y. -C. Lin, M. Clauß and M. Middendorf, "Simple Probabilistic Population-Based Optimization," in IEEE Transactions on Evolutionary Computation, vol. 20, no. 2, pp. 245-262, April 2016, doi: 10.1109/TEVC.2015.2451701.
[4] R. L. Haupt, "An introduction to genetic algorithms for electromagnetics," in IEEE Antennas and Propagation Magazine, vol. 37, no. 2, pp. 7-15, April 1995, doi: 10.1109/74.382334.
[5] S. M. Mikki and A. A. Kishk, "Quantum Particle Swarm Optimization for Electromagnetics," in IEEE Transactions on Antennas and Propagation, vol. 54, no. 10, pp. 2764-2775, Oct. 2006, doi: 10.1109/TAP.2006.882165.
[6] E. Boudaher and A. Hoorfar, "Electromagnetic optimization using mixed-parameter and multiobjective covariance matrix adaptation evolution strategy," IEEE Transactions on Antennas and Propagation, vol. 63, no. 4, pp. 1712–1724, 2015, doi: 10.1109/tap.2015.2398116.
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[8] K. Kaboutari, A. Zabihi, B. Virdee and M. Salmasi, "Microstrip patch antenna array with cosecant-squared radiation pattern profile," AEU - International Journal of Electronics and Communications, vol. 106, pp. 82–88, 2019, doi: 10.1016/j.aeue.2019.05.003.
[9] M.H. Teimouri, C. Ghobadi, J. Nourinia, K. Kaboutari, M. Shokri, B.S. Virdee, "Broadband printed dipole antenna with integrated balun and tuning element for DTV application,". AEU - International Journal of Electronics and Communications, vol. 148, p. 154161, 2022, doi: 10.1016/j.aeue.2022.154161.
[10] M. Shokri et al., "A Printed Dipole Antenna for WLAN Applications with Anti-interference Functionality," Photonics & Electromagnetics Research Symposium (PIERS), Hangzhou, China, 2021, pp. 1486-1494, doi: 10.1109/PIERS53385.2021.9694670.
[11] M. Hasan and H. Mouftah, "Optimization of watchdog selection in wireless sensor networks," IEEE Wireless Communications Letters, vol. 6, no. 1, pp. 94–97, 2016, doi: 10.1109/lwc.2016.2633990.
[12] L. Cao, Y. Cai and Y. Yue, "Swarm Intelligence-Based Performance Optimization for Mobile Wireless Sensor Networks: Survey, Challenges, and Future Directions," in IEEE Access, vol. 7, pp. 161524-161553, 2019, doi: 10.1109/ACCESS.2019.2951370.
[13] D. Cao, A. Modiri, G. Sureka and K. Kiasaleh, "DSP implementation of the particle swarm and genetic algorithms for real-time design of thinned array antennas," IEEE Antennas and Wireless Propagation Letters, vol. 11, pp. 1170–1173, 2012, doi: 10.1109/lawp.2012.2220514.
[14] A. Modiri and K. Kiasaleh, "Modification of real-number and binary pso algorithms for accelerated convergence," IEEE Transactions on Antennas and Propagation, vol. 59, no.1, pp. 214–224, 2011, doi: 10.1109/tap.2010.2090460.
[15] F. Grimaccia, M. Mussetta and R. Zich, "Genetical swarm optimization: Self-adaptive hybrid evolutionary algorithm for electromagnetics," IEEE Transactions on Antennas and Propagation, vol. 55, no. 3, pp. 781–785, 2007, doi: 10.1109/tap.2007.891561.
[16] A. Minasian and T. Bird, "Particle swarm optimization of microstrip antennas for wireless communication systems," IEEE Transactions on Antennas and Propagation, vol. 61, no. 12, pp. 6214–6217, 2013, doi: 10.1109/tap.2013.2281517.
[17] B. Tütüncü, "Compact low radar cross-section microstrip patch antenna using particle swarm optimization," Microwave and Optical Technology Letters, vol. 61, pp. 2288–2294, 2019, doi: 10.1002/mop.31893.
[18] Z. Bayraktar, P. L. Werner and D. H. Werner, "The design of miniature three-element stochastic yagi-uda arrays using particle swarm optimization," IEEE Antennas and Wireless Propagation Letters, vol. 5, pp. 22–26, 2006, doi: 10.1109/lawp.2005.863618.
[19] D. Ustun, A. Toktas and A. Akdagli, “Deep neural network–based soft computing the resonant frequency of E–shaped patch antennas,” AEU - International Journal of Electronics and Communications, vol. 102, pp. 54–61, 2019, doi: 10.1016/j.aeue.2019.02.011.
[20] G. Singh and U. Singh, “Triple band-notched UWB antenna design using a novel hybrid optimization technique based on DE and NMR algorithms,” Expert Systems with Applications, vol. 184, p. 115299, 2021, doi :10.1016/j.eswa.2021.115299.
[21] W.T. Li, X.W. Shi, Y.Q. Hei, S.F. Liu and J. Zhu, "A Hybrid Optimization Algorithm and Its Application for Conformal Array Pattern Synthesis," IEEE Transactions on Antennas and Propagation, vol. 58, no. 10, pp. 3401–3406, 2010, doi: 10.1109/TAP.2010.2050425.
[22] V. Hosseini, Y. Farhang, K. Majidzadeh and Ch. Ghobadi, “Customized mutated PSO algorithm of isolation enhancement for printed MIMO antenna with ISM band applications,” AEU - International Journal of Electronics and Communications, vol. 145, p. 154067, 2022, doi: 10.1016/j.aeue.2021.154067.
[23] V. Hosseini, Y. Farhang, K. Majidzadeh and Ch. Ghobadi, "Multi-Objective Hybrid Optimization Algorithm for Design a Printed MIMO Antenna With n78–5G NR Frequency Band Applications," in IEEE Access, vol. 11, pp. 68231-68242, 2023, doi: 10.1109/ACCESS.2023.3292307.
[24] V. Hosseini, F. Shapour, P. Pinho, Y. Farhang, K. Majidzadeh, Ch. Ghobadi, J. Nourinia, S. Barshandeh, M. Shokri, Zh. Amiri, M. Jalilirad and K. Kaboutari, “Dual-Band Planar Microstrip Monopole Antenna Design using Multi-Objective Hybrid Optimization Algorithm,” Photonics & Electromagnetics Research Symposium (PIERS), Prague, Republic of Czech, 2023, doi: 10.1109/PIERS59004.2023.10221360.
[25] M. Masdari, S. Barshande and S. Ozdemir, "CDABC: chaotic discrete artifcial bee colony algorithm for multi level clustering in large scale WSNs," J Supercomput., vol. 75, pp. 7174–7208, 2019, doi: 10.1007/s11227-019-02933-3.
[26] S. Barshandeh and M. Haghzadeh, "A new hybrid chaotic atom search optimization based on tree‑seed algorithm and Levy flight for solving optimization problems," Engineering with Computers, vol. 37, pp. 3079–3122, 2021, doi: 10.1007/s00366-020-00994-0.
_||_[1] M. Wetter and J. Wright, “A comparison of deterministic and probabilistic optimization algorithms for no smooth simulation-based optimization,” Building and Environment, vol. 39, no. 8, pp. 989–999, 2004, doi: 10.1016/j.buildenv.2004.01.022.
[2] S. Jin, H. Lee and J. Jeong, "Fast partial distortion elimination algorithm based on hadamard probability model," Electronics Letters, vol. 44, no. 1, pp. 11-17, doi: 10.1049/el:20082872.
[3] Y. -C. Lin, M. Clauß and M. Middendorf, "Simple Probabilistic Population-Based Optimization," in IEEE Transactions on Evolutionary Computation, vol. 20, no. 2, pp. 245-262, April 2016, doi: 10.1109/TEVC.2015.2451701.
[4] R. L. Haupt, "An introduction to genetic algorithms for electromagnetics," in IEEE Antennas and Propagation Magazine, vol. 37, no. 2, pp. 7-15, April 1995, doi: 10.1109/74.382334.
[5] S. M. Mikki and A. A. Kishk, "Quantum Particle Swarm Optimization for Electromagnetics," in IEEE Transactions on Antennas and Propagation, vol. 54, no. 10, pp. 2764-2775, Oct. 2006, doi: 10.1109/TAP.2006.882165.
[6] E. Boudaher and A. Hoorfar, "Electromagnetic optimization using mixed-parameter and multiobjective covariance matrix adaptation evolution strategy," IEEE Transactions on Antennas and Propagation, vol. 63, no. 4, pp. 1712–1724, 2015, doi: 10.1109/tap.2015.2398116.
[7] S. M. Mikki and A.A. Kishk, "Particle swarm optimization: A physics-based approach," Synthesis Lectures on Computational Electromagnetics, vol. 3, pp. 1–103, 2008, doi: 10.2200/s00110ed1v01y200804cem020.
[8] K. Kaboutari, A. Zabihi, B. Virdee and M. Salmasi, "Microstrip patch antenna array with cosecant-squared radiation pattern profile," AEU - International Journal of Electronics and Communications, vol. 106, pp. 82–88, 2019, doi: 10.1016/j.aeue.2019.05.003.
[9] M.H. Teimouri, C. Ghobadi, J. Nourinia, K. Kaboutari, M. Shokri, B.S. Virdee, "Broadband printed dipole antenna with integrated balun and tuning element for DTV application,". AEU - International Journal of Electronics and Communications, vol. 148, p. 154161, 2022, doi: 10.1016/j.aeue.2022.154161.
[10] M. Shokri et al., "A Printed Dipole Antenna for WLAN Applications with Anti-interference Functionality," Photonics & Electromagnetics Research Symposium (PIERS), Hangzhou, China, 2021, pp. 1486-1494, doi: 10.1109/PIERS53385.2021.9694670.
[11] M. Hasan and H. Mouftah, "Optimization of watchdog selection in wireless sensor networks," IEEE Wireless Communications Letters, vol. 6, no. 1, pp. 94–97, 2016, doi: 10.1109/lwc.2016.2633990.
[12] L. Cao, Y. Cai and Y. Yue, "Swarm Intelligence-Based Performance Optimization for Mobile Wireless Sensor Networks: Survey, Challenges, and Future Directions," in IEEE Access, vol. 7, pp. 161524-161553, 2019, doi: 10.1109/ACCESS.2019.2951370.
[13] D. Cao, A. Modiri, G. Sureka and K. Kiasaleh, "DSP implementation of the particle swarm and genetic algorithms for real-time design of thinned array antennas," IEEE Antennas and Wireless Propagation Letters, vol. 11, pp. 1170–1173, 2012, doi: 10.1109/lawp.2012.2220514.
[14] A. Modiri and K. Kiasaleh, "Modification of real-number and binary pso algorithms for accelerated convergence," IEEE Transactions on Antennas and Propagation, vol. 59, no.1, pp. 214–224, 2011, doi: 10.1109/tap.2010.2090460.
[15] F. Grimaccia, M. Mussetta and R. Zich, "Genetical swarm optimization: Self-adaptive hybrid evolutionary algorithm for electromagnetics," IEEE Transactions on Antennas and Propagation, vol. 55, no. 3, pp. 781–785, 2007, doi: 10.1109/tap.2007.891561.
[16] A. Minasian and T. Bird, "Particle swarm optimization of microstrip antennas for wireless communication systems," IEEE Transactions on Antennas and Propagation, vol. 61, no. 12, pp. 6214–6217, 2013, doi: 10.1109/tap.2013.2281517.
[17] B. Tütüncü, "Compact low radar cross-section microstrip patch antenna using particle swarm optimization," Microwave and Optical Technology Letters, vol. 61, pp. 2288–2294, 2019, doi: 10.1002/mop.31893.
[18] Z. Bayraktar, P. L. Werner and D. H. Werner, "The design of miniature three-element stochastic yagi-uda arrays using particle swarm optimization," IEEE Antennas and Wireless Propagation Letters, vol. 5, pp. 22–26, 2006, doi: 10.1109/lawp.2005.863618.
[19] D. Ustun, A. Toktas and A. Akdagli, “Deep neural network–based soft computing the resonant frequency of E–shaped patch antennas,” AEU - International Journal of Electronics and Communications, vol. 102, pp. 54–61, 2019, doi: 10.1016/j.aeue.2019.02.011.
[20] G. Singh and U. Singh, “Triple band-notched UWB antenna design using a novel hybrid optimization technique based on DE and NMR algorithms,” Expert Systems with Applications, vol. 184, p. 115299, 2021, doi :10.1016/j.eswa.2021.115299.
[21] W.T. Li, X.W. Shi, Y.Q. Hei, S.F. Liu and J. Zhu, "A Hybrid Optimization Algorithm and Its Application for Conformal Array Pattern Synthesis," IEEE Transactions on Antennas and Propagation, vol. 58, no. 10, pp. 3401–3406, 2010, doi: 10.1109/TAP.2010.2050425.
[22] V. Hosseini, Y. Farhang, K. Majidzadeh and Ch. Ghobadi, “Customized mutated PSO algorithm of isolation enhancement for printed MIMO antenna with ISM band applications,” AEU - International Journal of Electronics and Communications, vol. 145, p. 154067, 2022, doi: 10.1016/j.aeue.2021.154067.
[23] V. Hosseini, Y. Farhang, K. Majidzadeh and Ch. Ghobadi, "Multi-Objective Hybrid Optimization Algorithm for Design a Printed MIMO Antenna With n78–5G NR Frequency Band Applications," in IEEE Access, vol. 11, pp. 68231-68242, 2023, doi: 10.1109/ACCESS.2023.3292307.
[24] V. Hosseini, F. Shapour, P. Pinho, Y. Farhang, K. Majidzadeh, Ch. Ghobadi, J. Nourinia, S. Barshandeh, M. Shokri, Zh. Amiri, M. Jalilirad and K. Kaboutari, “Dual-Band Planar Microstrip Monopole Antenna Design using Multi-Objective Hybrid Optimization Algorithm,” Photonics & Electromagnetics Research Symposium (PIERS), Prague, Republic of Czech, 2023, doi: 10.1109/PIERS59004.2023.10221360.
[25] M. Masdari, S. Barshande and S. Ozdemir, "CDABC: chaotic discrete artifcial bee colony algorithm for multi level clustering in large scale WSNs," J Supercomput., vol. 75, pp. 7174–7208, 2019, doi: 10.1007/s11227-019-02933-3.
[26] S. Barshandeh and M. Haghzadeh, "A new hybrid chaotic atom search optimization based on tree‑seed algorithm and Levy flight for solving optimization problems," Engineering with Computers, vol. 37, pp. 3079–3122, 2021, doi: 10.1007/s00366-020-00994-0.