Skip to main content

Advertisement

SpringerLink
Log in

RETRACTED ARTICLE: A Novel Adaptive Sliding Mode Control of Microbial Fuel Cell in the Presence of Uncertainty

  • Original Article
  • Published:
Journal of Electrical Engineering & Technology Aims and scope Submit manuscript

This article was retracted on 02 May 2023

This article has been updated

Abstract

Model-based control strategies for microbial fuel cell are able to create a balance between fuel supply, mass, charge and electric charge, performance efficiency. This paper designs a new adaptive sliding mode control scheme of single chamber single population microbial fuel cell. The adaptive method estimates parametric uncertainty and nonlinear terms while the sliding mode method achieves microbial fuel cell performance targets. The significant advantage of the suggested scheme is its capability to provide robustness against parametric uncertainties and handle systems nonlinearity. The Lyapunov technique has been used to demonstrate robust stability in the face of nonlinearity and uncertainty. Numerical simulations confirms that the proposed control method is able to meet the desired specification in the presence of varieties of parametric uncertainty.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Change history

References

  1. Du Z, Li H, Gu T (2007) A state of the art review on microbial fuel cells: a promising technology for wastewater treatment and bioenergy. Biotechnol Adv 25:464–482

    Article  Google Scholar 

  2. Davis F, Higson SPJ (2007) Biofuel cells—recent advances and applications. Biosens Bioelectron 22:1224–1235

    Article  Google Scholar 

  3. Granqvist CG (2007) Transparent conductors as solar energy materials: a panoramic review. Sol Energy Mater Sol Cells 91:1529–1598

    Article  Google Scholar 

  4. Herbert GJ, Iniyan S, Sreevalsan E, Rajapandian S (2007) A review of wind energy technologies. Renew Sustain Energy Rev 11:1117–1145

    Article  Google Scholar 

  5. Antonio FdO (2010) Wave energy utilization: a review of the technologies. Renew Sustain Energy Rev 14:899–918

    Article  Google Scholar 

  6. Lund JW, Freeston DH, Boyd TL (2011) Direct utilization of geothermal energy 2010 worldwide review. Geothermics 40:159–180

    Article  Google Scholar 

  7. Berndes G, Hoogwijk M, van den Broek R (2003) The contribution of biomass in the future global energy supply: a review of 17 studies. Biomass Bioenergy 25:1–28

    Article  Google Scholar 

  8. Khare V, Nema S, Baredar P (2016) Solar–wind hybrid renewable energy system: a review. Renew Sustain Energy Rev 58:23–33

    Article  Google Scholar 

  9. An J, Sim J, Lee HS (2015) Control of voltage reversal in serially stacked microbial fuel cells through manipulating current: significance of critical current density. J Power Sources 283:19–23

    Article  Google Scholar 

  10. Andersen SJ, Pikaar I, Freguia S, Lovell BC, Rabaey K, Rozendal RA (2013) Dynamically adaptive control system for bioanodes in serially stacked bioelectrochemical systems. Environ Sci Technol 47(10):5488–5494

    Article  Google Scholar 

  11. Zeng Y, Choo YF, Kim BH, Wu P (2010) Modelling and simulation of two-chamber microbial fuel cell. J Power Sources 195(1):79–89

    Article  Google Scholar 

  12. Abul A, Zhang J, Steidl R, Reguera G, Tan X (2016) Microbial fuel cells: Control-oriented modeling and experimental validation. In 2016 American Control Conference (ACC) IEEE, pp. 412–417

  13. Pinto RP, Srinivasan B, Manuel MF, Tartakovsky B (2010) A two-population bio-electrochemical model of a microbial fuel cell. Bioresour Technol 101(14):5256–5265

    Article  Google Scholar 

  14. Patel R, Deb D (2018) Parametrized control-oriented mathematical model and adaptive backstepping control of a single chamber single population microbial fuel cell. J Power Sources 396:599–605

    Article  Google Scholar 

  15. Ortiz-Martínez VM, Salar-García MJ, De Los Ríos AP, Hernández-Fernández FJ, Egea JA, Lozano LJ (2015) Developments in microbial fuel cell modeling. Chem Eng J 271:50–60

    Article  Google Scholar 

  16. Recio-Garrido D, Perrier M, Tartakovsky B (2016) Modeling, optimization and control of bioelectrochemical systems. Chem Eng J 289:180–190

    Article  Google Scholar 

  17. Boghani HC, Michie I, Dinsdale RM, Guwy AJ, Premier GC (2016) Control of microbial fuel cell voltage using a gain scheduling control strategy. J Power Sources 322:106–115

    Article  Google Scholar 

  18. Recio-Garrido D, Tartakovsky B, Perrier M (2016) Staged microbial fuel cells with periodic connection of external resistance. IFAC-PapersOnLine 49(7):91–96

    Article  Google Scholar 

  19. Yan M, Fan L (2013) Constant voltage output in two-chamber microbial fuel cell under fuzzy PID control. Int J Electrochem Sci 8(3):3321–3332

    Google Scholar 

  20. Fan L, Li C, Boshnakov K (2014) Performance improvement of a Microbial fuel cell based on adaptive fuzzy control. Pak J Pharma Sci 27(3):685–690

    Google Scholar 

  21. Fan L, Zhang J, Shi X (2015) Performance improvement of a microbial fuel cell based on model predictive control. Int J Electrochem Sci 10(1):737–748

    Google Scholar 

  22. Patel R, Deb D (2017) Control-oriented parametrized models for microbial fuel cells. In 2017 6th International conference on computer applications in electrical engineering-recent advances (CERA), IEEE, pp. 152–157

  23. Shi X, Cheng Y, Yin C, Huang X, Zhong SM (2019) Design of adaptive backstepping dynamic surface control method with RBF neural network for uncertain nonlinear system. Neurocomputing 330:490–503

    Article  Google Scholar 

  24. Yu H, Jing Y, Zhang S (2016) Complexity explosion problem analysis and development in back-stepping method. In 2016 Chinese control and decision conference (CCDC), IEEE, pp. 1753–1758

  25. Ghanavati M, Salahshoor K, Jahed Motlagh MR, Ramezani A, Moarefianpour A (2017) A novel robust generalized backstepping controlling method for a class of nonlinear systems. Cogent Eng 4(1):1342309

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin, 132022, China

    Xiuwei Fu & Li Fu

  2. Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran

    Hashem Imani Marrani

Authors
  1. Xiuwei Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hashem Imani Marrani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Li Fu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s42835-023-01509-9"

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fu, X., Fu, L. & Imani Marrani, H. RETRACTED ARTICLE: A Novel Adaptive Sliding Mode Control of Microbial Fuel Cell in the Presence of Uncertainty. J. Electr. Eng. Technol. 15, 2769–2776 (2020). https://doi.org/10.1007/s42835-020-00535-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42835-020-00535-1

Keywords

Search

Navigation