IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v172y2023ics0960077923004423.html
   My bibliography  Save this article

Theoretical analysis and experimental verification of fractional-order RC cobweb circuit network

Author

Listed:
  • Liu, Yang
  • Chen, Liping
  • Wu, Xiaobo
  • Lopes, António M.
  • Cui, Fengqi
  • Chen, YangQuan

Abstract

Recent research has shown that ideal capacitors and inductors do not physically exist, and that the dynamics of real devices can be accurately described by fractional-order (FO) mathematical models. This paper investigates a class of 2×n order RC cobweb FO circuit network with central node. Based on the Kirchhoff’s laws, the impedance magnitude and phase between two points of the network are derived using difference equations and matrix transformations. Three impedance expressions are deduced, and their correctness is verified numerically and by simulations. The influence of various parameters of the electrical network, namely the resistance, capacitance, number of circuit units, frequency and fractional order, on the impedance is studied. Additionally, for the first time, physical experiments are presented to compare the effectiveness of FO and integer-order circuit networks for describing the impedance of actual physical circuits. These experiments confirm that FO circuit network models perform better than the integer-order ones for representing the characteristics of the impedance magnitude and phase.

Suggested Citation

  • Liu, Yang & Chen, Liping & Wu, Xiaobo & Lopes, António M. & Cui, Fengqi & Chen, YangQuan, 2023. "Theoretical analysis and experimental verification of fractional-order RC cobweb circuit network," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
  • Handle: RePEc:eee:chsofr:v:172:y:2023:i:c:s0960077923004423
    DOI: 10.1016/j.chaos.2023.113541
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923004423
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2023.113541?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chu, Yu-Ming & Bekiros, Stelios & Zambrano-Serrano, Ernesto & Orozco-López, Onofre & Lahmiri, Salim & Jahanshahi, Hadi & Aly, Ayman A., 2021. "Artificial macro-economics: A chaotic discrete-time fractional-order laboratory model," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    2. F. Merrikh Bayat & M. Prezioso & B. Chakrabarti & H. Nili & I. Kataeva & D. Strukov, 2018. "Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits," Nature Communications, Nature, vol. 9(1), pages 1-7, December.
    3. Ahmad, Shabir & Ullah, Aman & Al-Mdallal, Qasem M. & Khan, Hasib & Shah, Kamal & Khan, Aziz, 2020. "Fractional order mathematical modeling of COVID-19 transmission," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    4. Amir Bashan & Ronny P. Bartsch & Jan. W. Kantelhardt & Shlomo Havlin & Plamen Ch. Ivanov, 2012. "Network physiology reveals relations between network topology and physiological function," Nature Communications, Nature, vol. 3(1), pages 1-9, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shekhtman, Louis M. & Danziger, Michael M. & Havlin, Shlomo, 2016. "Recent advances on failure and recovery in networks of networks," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 28-36.
    2. Ullah, Mohammad Sharif & Higazy, M. & Kabir, K.M. Ariful, 2022. "Dynamic analysis of mean-field and fractional-order epidemic vaccination strategies by evolutionary game approach," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    3. Alkhazzan, Abdulwasea & Wang, Jungang & Nie, Yufeng & Khan, Hasib & Alzabut, Jehad, 2023. "An effective transport-related SVIR stochastic epidemic model with media coverage and Lévy noise," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    4. Maurício de Carvalho, João P.S. & Moreira-Pinto, Beatriz, 2021. "A fractional-order model for CoViD-19 dynamics with reinfection and the importance of quarantine," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    5. Bumhee Park & Dae-Shik Kim & Hae-Jeong Park, 2014. "Graph Independent Component Analysis Reveals Repertoires of Intrinsic Network Components in the Human Brain," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    6. Yeh, Chien-Hung & Lo, Men-Tzung & Hu, Kun, 2016. "Spurious cross-frequency amplitude–amplitude coupling in nonstationary, nonlinear signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 143-150.
    7. Kumar, Pushpendra & Erturk, Vedat Suat, 2021. "Environmental persistence influences infection dynamics for a butterfly pathogen via new generalised Caputo type fractional derivative," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    8. Wang, Yanjun & Li, Max Z. & Gopalakrishnan, Karthik & Liu, Tongdan, 2022. "Timescales of delay propagation in airport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    9. Wang, Yupin & Li, Xiaodi & Wang, Da & Liu, Shutang, 2022. "A brief note on fractal dynamics of fractional Mandelbrot sets," Applied Mathematics and Computation, Elsevier, vol. 432(C).
    10. Alexander Domoshnitsky & Alexander Sitkin & Lea Zuckerman, 2022. "Mathematical Modeling of COVID-19 Transmission in the Form of System of Integro-Differential Equations," Mathematics, MDPI, vol. 10(23), pages 1-17, November.
    11. Ahmad, Shabir & Ullah, Aman & Akgül, Ali, 2021. "Investigating the complex behaviour of multi-scroll chaotic system with Caputo fractal-fractional operator," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    12. Jianxi Gao & Xueming Liu & Daqing Li & Shlomo Havlin, 2015. "Recent Progress on the Resilience of Complex Networks," Energies, MDPI, vol. 8(10), pages 1-24, October.
    13. Khatun, Mst Sebi & Das, Samhita & Das, Pritha, 2023. "Dynamics and control of an SITR COVID-19 model with awareness and hospital bed dependency," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    14. Wang, Bo & Liu, Jinping & Alassafi, Madini O. & Alsaadi, Fawaz E. & Jahanshahi, Hadi & Bekiros, Stelios, 2022. "Intelligent parameter identification and prediction of variable time fractional derivative and application in a symmetric chaotic financial system," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    15. Dror Kenett & Shlomo Havlin, 2015. "Network science: a useful tool in economics and finance," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 14(2), pages 155-167, November.
    16. David Jiménez-Grande & S Farokh Atashzar & Eduardo Martinez-Valdes & Deborah Falla, 2021. "Muscle network topology analysis for the classification of chronic neck pain based on EMG biomarkers extracted during walking," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-17, June.
    17. Amar Nath Chatterjee & Fahad Al Basir & Bashir Ahmad & Ahmed Alsaedi, 2022. "A Fractional-Order Compartmental Model of Vaccination for COVID-19 with the Fear Factor," Mathematics, MDPI, vol. 10(9), pages 1-15, April.
    18. Arshad, Sadia & Siddique, Imran & Nawaz, Fariha & Shaheen, Aqila & Khurshid, Hina, 2023. "Dynamics of a fractional order mathematical model for COVID-19 epidemic transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    19. Shchanikov, Sergey & Zuev, Anton & Bordanov, Ilya & Danilin, Sergey & Lukoyanov, Vitaly & Korolev, Dmitry & Belov, Alexey & Pigareva, Yana & Gladkov, Arseny & Pimashkin, Alexey & Mikhaylov, Alexey & K, 2021. "Designing a bidirectional, adaptive neural interface incorporating machine learning capabilities and memristor-enhanced hardware," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    20. Koutou, Ousmane & Diabaté, Abou Bakari & Sangaré, Boureima, 2023. "Mathematical analysis of the impact of the media coverage in mitigating the outbreak of COVID-19," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 600-618.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:172:y:2023:i:c:s0960077923004423. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.