Skip to main content
Log in

Fault estimation observer design for fractional-order financial system subject to time-delay

  • Published:
International Journal of Dynamics and Control Aims and scope Submit manuscript

Abstract

This article is devoted to resolving the issue of time-varying fault in the fractional-order financial system subject to constant delay. A fault-tolerant control is addressed to solve the faults which occur by unpredictable affairs in the financial system. Further, a set of adequate constraints in the form of Linear Matrix Inequalities are derived to ensure asymptotic stability of the considered system under the theorem of Lyapunov. More precisely, Lyapunov–Krasovskii candidates are employed independently with various state-space trajectories such as interest rate, investment demand and price index. Lastly, a numerical example is provided to support the constructed theoretical results.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Tacha OI, Volos CK, Kyprianidis IM, Stouboulos IN, Vaidyanathan S, Pham VT (2016) Analysis, adaptive control and circuit simulation of a novel nonlinear finance system. Appl Math Comput 276:200–217

    MathSciNet  MATH  Google Scholar 

  2. Vaidyanathan S, Volos CK, Tacha OI, Kyprianidis IM, Stouboulos IN, Pham VT (2016) Analysis, control and circuit simulation of a novel 3-D finance chaotic system. Adv Appl Chaotic Syst 636:495–512

    Article  Google Scholar 

  3. Hajipour A, Tavakoli H (2017) Dynamic analysis and adaptive sliding mode controller for a chaotic fractional incommensurate order financial system. Int J Bifurc Chaos 27(13):1750198

    Article  MathSciNet  Google Scholar 

  4. Hajipour A, Hajipour M, Baleanu D (2018) On the adaptive sliding mode controller for a hyperchaotic fractional-order financial system. Phys A 497:139–153

    Article  MathSciNet  Google Scholar 

  5. Camacho NA, Mermoud MAD, Gallegos JA (2014) Lyapunov functions for fractional order systems. Commun Nonlinear Sci Numer Simul 19(9):2951–2957

    Article  MathSciNet  Google Scholar 

  6. Boroujeni EA, Momeni HR (2012) Observer based control of a class of nonlinear fractional order systems using LMI. Int J Sci Eng Investig 1(1):48–52

    Google Scholar 

  7. Zhang ES, Yu Y, Yu J (2017) LMI conditions for global stability of fractional-order neural networks. IEEE Trans Neural Netw Learn Syst 28(10):2423–2433

    Article  MathSciNet  Google Scholar 

  8. Li H, Li S, Lia G, Wang H (2017) Robust adaptive control for fractional-order financial chaotic systems with system uncertainties and external disturbances. J Inf Technol Control 46(2):246–259

  9. Zhang Z, Zhang J, Cheng F, Xu Y (2019) Bifurcation analysis and stability criterion for the nonlinear fractional-order three-dimensional financial system with delay. Asian J Control 21(6):1–11

    MathSciNet  Google Scholar 

  10. Huang C, Cao J (2017) Active control strategy for synchronization and anti-synchronization of a fractional chaotic financial system. Phys A 473:262–275

    Article  MathSciNet  Google Scholar 

  11. Dhanalakshmi P, Senpagam S, Mohanapriya R (2019) Robust fault estimation controller for fractional-order delayed system using quantized measurement. Int J Dyn Control. https://doi.org/10.1007/s40435-019-00549-2

  12. You F, Li H, Wang F, Guan S, Zhang K (2015) Robust fast adaptive fault estimation for systems with time-varying interval delay. J Frankl Inst 352:5486–5513

    Article  MathSciNet  Google Scholar 

  13. You F, Li H, Wang F, Guan S, Zhang K (2015) Fractional-order adaptive fault estimation for a class of nonlinear fractional-order systems. In: 2015 American control conference (ACC). Chicago, IL, pp 3804–3809

  14. Han J, Zhang H, Wang Y, Zhang K (2018) Fault estimation and fault-tolerant control for switched fuzzy stochastic systems. IEEE Trans Fuzzy Syst 26(5):2993–3003

    Article  Google Scholar 

  15. Li X, Ahn CK, Lu D, Guo S (2019) Robust simultaneous fault estimation and nonfragile output feedback fault-tolerant control for markovian jump systems. IEEE Trans Syst Man Cybern Syst 49(9):1769–1776

    Article  Google Scholar 

  16. Vara RC, Novais P, Gil AB, Prieto J, Corchado JM (2019) Distributed continuous-time fault estimation control for multiple devices in IoT networks. IEEE Access 7:11972–11984

    Article  Google Scholar 

  17. Zhang H, Ye R, Cao J, Alsaedi A (2018) Delay-independent stability of Riemann–Liouville fractional neutral-type delayed neural networks. Neural Process Lett 42:427–442

    Google Scholar 

  18. Li Y, Chen YQ, Podlubny I (2010) Stability of fractional-order nonlinear dynamic systems: Lyapunov direct method and generalized Mittag–Leffler stability. Comput Math Appl 59:1810–1821

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

This research work of S. Senpagam is financially supported by Department of Science and Technology(DST)-Promotion of University Research and Scientific Excellence(PURSE) Phase-II, Government of India, New Delhi.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to P. Dhanalakshmi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Senpagam, S., Dhanalakshmi, P. & Mohanapriya, R. Fault estimation observer design for fractional-order financial system subject to time-delay. Int. J. Dynam. Control 9, 190–198 (2021). https://doi.org/10.1007/s40435-020-00642-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40435-020-00642-x

Keywords

Navigation