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Parameter identification of fractional-order chaotic systems using different Meta-heuristic Optimization Algorithms

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Abstract

Fractional-order chaotic systems (FOCS) parameter identification is an essential issue in chaos control and synchronization process. In this paper, different recent Meta-heuristic Optimization Algorithms are used to estimate the parameters and orders of three FOCS. The investigated systems are Arneodo, Borah rotational attractor and Chen double- and four-wing systems. The employed algorithms are the Salp Swarm Algorithm, Whale Optimization Algorithm, Moth-Flame Optimizer, Grey Wolf Optimizer and the Flower Pollination Algorithm (FPA). The proposed algorithms are applied on several objective functions to identify the FOCS parameters including Mean Square Error (MSE), Integral of Squared Error (ISE), Integral of Absolute Error and Integral of Time Absolute Error. A comparison between the obtained results from each algorithm over each employed objective function is carried out. The target is to investigate the most adequate optimization technique in this difficult multidimensional problem and the best objective function that helps the algorithms capture more accurate and consistent results. The performance of optimization algorithms in the presence of measurement noise has been tested using two objective functions (MSE and ISE) for the three chaotic systems. The overall outcome shows that FPA with ISE objective function is the most efficient combination for the parameter identification of the three FOCS without/with noise because it achieves higher accuracy and more robust results with faster convergence speeds than all other algorithms.

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References

  1. AbdelAty, A.M., Azar, A.T., Vaidyanathan, S., Ouannas, A., Radwan, A.G.: Chapter 14—applications of continuous-time fractional order chaotic systems. In: Azar, A.T., Radwan, A.G., Vaidyanathan, S. (eds.) Mathematical Techniques of Fractional Order Systems, Advances in Nonlinear Dynamics and Chaos (ANDC), pp. 409–449. Elsevier, Amsterdam (2018)

    Chapter  Google Scholar 

  2. AbdelAty, A.M., Elwakil, A.S., Radwan, A.G., Psychalinos, C., Maundy, B.J.: Approximation of the fractional-order laplacian \(s^\alpha \) as a weighted sum of first-order high-pass filters. IEEE Trans. Circuits Syst. II Express Briefs 65(8), 1114–1118 (2018)

  3. AbdelAty, A.M., Radwan, A.G., Elwakil, A.S., Psychalinos, C.: Transient and steady-state response of a fractional-order dynamic PV model under different loads. J. Circuits Syst. Comput. (2018). https://doi.org/10.1142/S0218126618500238

  4. AboBakr, A., Said, L.A., Madian, A.H., Elwakil, A.S., Radwan, A.G.: Experimental comparison of integer/fractional-order electrical models of plant. AEU Int. J. Electron. Commun. 80, 1–9 (2017)

    Article  Google Scholar 

  5. Aghababa, M.P.: Finite-time chaos control and synchronization of fractional-order nonautonomous chaotic (hyperchaotic) systems using fractional nonsingular terminal sliding mode technique. Nonlinear Dyn. 69(1), 247–261 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  6. Alam, D., Yousri, D., Eteiba, M.: Flower pollination algorithm based solar pv parameter estimation. Energy Convers. Manag. 101, 410–422 (2015)

    Article  Google Scholar 

  7. Alfi, A.: Particle swarm optimization algorithm with dynamic inertia weight for online parameter identification applied to lorenz chaotic system. Int. J. Innov. Comput. Inf. Control 8(2), 1191–1203 (2012)

    Google Scholar 

  8. Allam, D., Yousri, D., Eteiba, M.: Parameters extraction of the three diode model for the multi-crystalline solar cell/module using moth-flame optimization algorithm. Energy Convers. Manag. 123, 535–548 (2016)

    Article  Google Scholar 

  9. Arneodo, A., Coullet, P., Spiegel, E., Tresser, C.: Asymptotic chaos. Physica D Nonlinear Phenom. 14(3), 327–347 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  10. Behinfaraz, R., Badamchizadeh, M., Ghiasi, A.R.: An adaptive method to parameter identification and synchronization of fractional-order chaotic systems with parameter uncertainty. Appl. Math. Model. 40(7), 4468–4479 (2016)

    Article  MathSciNet  Google Scholar 

  11. Borah, M., Roy, B.K.: Can fractional-order coexisting attractors undergo a rotational phenomenon? ISA Trans. 82, 2–17 (2018)

  12. Borah, M., Roy, B.K.: An enhanced multi-wing fractional-order chaotic system with coexisting attractors and switching hybrid synchronisation with its nonautonomous counterpart. Chaos Solitons Fractals 102, 372–386 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  13. Calame, J.: Molecular dynamics modeling of dielectric polarization and ferroelectricity in poly (vinylidene fluoride) and related polymers. InL APS Meeting Abstracts (2016)

  14. Chen, D., Wu, C., Iu, H.H.C., Ma, X.: Circuit simulation for synchronization of a fractional-order and integer-order chaotic system. Nonlinear Dyn. 73(3), 1671–1686 (2013)

    Article  MathSciNet  Google Scholar 

  15. Colinas-Armijo, N., Cutrona, S., Di Paola, M., Pirrotta, A.: Fractional viscoelastic beam under torsion. Commun. Nonlinear Sci. Numer. Simul. 48, 278–287 (2017)

    Article  MathSciNet  Google Scholar 

  16. Daftardar-Gejji, V., Bhalekar, S.: Chaos in fractional ordered Liu system. Comput. Math. Appl. 59(3), 1117–1127 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  17. Du, L., Zhao, Y., Lei, Y., Hu, J., Yue, X.: Suppression of chaos in a generalized duffing oscillator with fractional-order deflection. Nonlinear Dyn. 92(4), 1921–1933 (2018)

  18. Du, W., Miao, Q., Tong, L., Tang, Y.: Identification of fractional-order systems with unknown initial values and structure. Phys. Lett. A 381(23), 1943–1949 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  19. El-Fergany, A.A.: Extracting optimal parameters of pem fuel cells using salp swarm optimizer. Renew. Energy 119, 641–648 (2018)

    Article  Google Scholar 

  20. Elwakil, A.S., Allagui, A., Freeborn, T., Maundy, B.: Further experimental evidence of the fractional-order energy equation in supercapacitors. AEU Int. J. Electron. Commun. 78, 209–212 (2017)

    Article  Google Scholar 

  21. Hasanien, H.M.: Performance improvement of photovoltaic power systems using an optimal control strategy based on whale optimization algorithm. Electr. Power Syst. Res. 157, 168–176 (2018)

    Article  Google Scholar 

  22. He, S., Sun, K., Wang, H., Mei, X., Sun, Y.: Generalized synchronization of fractional-order hyperchaotic systems and its DSP implementation. Nonlinear Dyn. 92(1), 85–96 (2018)

    Article  Google Scholar 

  23. Huang, Y., Guo, F., Li, Y., Liu, Y.: Parameter estimation of fractional-order chaotic systems by using quantum parallel particle swarm optimization algorithm. PLOS One 10(1), e0114910 (2015)

    Article  Google Scholar 

  24. Ismail, S.M., Said, L.A., Radwan, A.G., Madian, A.H., Abu-ElYazeed, M.F., Soliman, A.M.: Generalized fractional logistic map suitable for data encryption. In: 2015 International Conference on Science and Technology (TICST), pp. 336–341. IEEE (2015)

  25. Ismail, S.M., Said, L.A., Rezk, A.A., Radwan, A.G., Madian, A.H., Abu-Elyazeed, M.F., Soliman, A.M.: Generalized fractional logistic map encryption system based on FPGA. AEU Int. J. Electron. Commun. 80, 114–126 (2017)

    Article  Google Scholar 

  26. Li, C.-L., Wu, L.: Sliding mode control for synchronization of fractional permanent magnet synchronous motors with finite time. Opt. Int. J. Light Electron Opt. 127(6), 3329–3332 (2016)

    Article  Google Scholar 

  27. Li, R.-G., Wu, H.-N.: Adaptive synchronization control based on QPSO algorithm with interval estimation for fractional-order chaotic systems and its application in secret communication. Nonlinear Dyn. 92(3), 935–959 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  28. Li, X., Yin, M.: Parameter estimation for chaotic systems by hybrid differential evolution algorithm and artificial bee colony algorithm. Nonlinear Dyn. 77(1–2), 61–71 (2014)

    Article  MathSciNet  Google Scholar 

  29. Lin, J.: Parameter estimation for time-delay chaotic systems by hybrid biogeography-based optimization. Nonlinear Dyn. 77(3), 983–992 (2014)

    Article  Google Scholar 

  30. Lin, J.: Oppositional backtracking search optimization algorithm for parameter identification of hyperchaotic systems. Nonlinear Dyn. 80(1–2), 209–219 (2015)

    Article  MathSciNet  Google Scholar 

  31. Lin, J., Chen, C.: Parameter estimation of chaotic systems by an oppositional seeker optimization algorithm. Nonlinear Dyn. 76(1), 509–517 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  32. Lin, J., Wang, Z.-J.: Parameter identification for fractional-order chaotic systems using a hybrid stochastic fractal search algorithm. Nonlinear Dyn. 90(2), 1243–1255 (2017)

    Article  MathSciNet  Google Scholar 

  33. Liu, H., Hua, G., Yin, H., Xu, Y.: An intelligent grey wolf optimizer algorithm for distributed compressed sensing. Comput. Intell. Neurosci. (2018). https://doi.org/10.1155/2018/1723191

  34. Lu, J.G.: Chaotic dynamics and synchronization of fractional-order arneodos systems. Chaos Solitons Fractals 26(4), 1125–1133 (2005)

    Article  MATH  Google Scholar 

  35. Mirjalili, S.: Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowl. Based Syst. 89, 228–249 (2015)

    Article  Google Scholar 

  36. Mirjalili, S., Gandomi, A.H., Mirjalili, S.Z., Saremi, S., Faris, H., Mirjalili, S.M.: Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv. Eng. Softw. 114, 163–191 (2017)

    Article  Google Scholar 

  37. Mirjalili, S., Lewis, A.: The whale optimization algorithm. Adv. Eng. Softw. 95, 51–67 (2016)

    Article  Google Scholar 

  38. Mirjalili, S., Mirjalili, S.M., Lewis, A.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46–61 (2014)

    Article  Google Scholar 

  39. Petráš, I.: Fractional-Order Nonlinear Systems. Springer, Berlin (2011)

    Book  MATH  Google Scholar 

  40. Podlubny, I.: Fractional Differential Equations: An Introduction to Fractional Derivatives, Fractional Differential Equations, to Methods of Their Solution and Some of Their Applications. Academic Press, New York (1999)

    MATH  Google Scholar 

  41. Precup, R.-E., David, R.-C., Petriu, E.M.: Grey wolf optimizer algorithm-based tuning of fuzzy control systems with reduced parametric sensitivity. IEEE Trans. Ind. Electron. 64(1), 527–534 (2017)

    Article  Google Scholar 

  42. Precup, R.-E., David, R.-C., Petriu, E.M., Szedlak-Stinean, A.-I., Bojan-Dragos, C.-A.: Grey wolf optimizer-based approach to the tuning of pi-fuzzy controllers with a reduced process parametric sensitivity. IFAC Pap. OnLine 49(5), 55–60 (2016)

    Article  Google Scholar 

  43. Radwan, A.G., Sayed, W.S., Abd-El-Hafiz, S.K.: Control and synchronization of fractional-order chaotic systems. In: Azar, A.T., Vaidyanathan, S., Ouannas, A. (eds.) Fractional Order Control and Synchronization of Chaotic Systems, pp. 325–355. Springer, Cham (2017)

    Chapter  MATH  Google Scholar 

  44. Said, L.A., Radwan, A.G., Madian, A.H., Soliman, A.M.: Fractional-order inverting and non-inverting filters based on CFOA. In: 2016 39th International Conference on Telecommunications and Signal Processing (TSP), pp. 599–602. IEEE (2016)

  45. Said, L.A., Radwan, A.G., Madian, A.H., Soliman, A.M.: Fractional order oscillator design based on two-port network. Circuits Syst. Signal Process. 35(9), 3086–3112 (2016)

    Article  MathSciNet  Google Scholar 

  46. Said, L.A., Radwan, A.G., Madian, A.H., Soliman, A.M.: Three fractional-order-capacitors-based oscillators with controllable phase and frequency. J. Circuits Syst. Comput. 26(10), 1750160 (2017)

    Article  Google Scholar 

  47. Sheng, Z., Wang, J., Zhou, S., Zhou, B.: Parameter estimation for chaotic systems using a hybrid adaptive cuckoo search with simulated annealing algorithm. Chaos Interdiscip. J. Nonlinear Sci. 24(1), 013133 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  48. Sheu, L.J., Chen, W.C., Chen, Y.C., Weng, W.T.: A two-channel secure communication using fractional chaotic systems. World Acad. Sci. Eng. Technol. 65, 1057–1061 (2010)

    Google Scholar 

  49. Singh, U., Salgotra, R.: Synthesis of linear antenna array using flower pollination algorithm. Neural Comput. Appl. 29(2), 435–445 (2018)

    Article  Google Scholar 

  50. Tabasi, M., Balochian, S.: Synchronization of the chaotic fractional-order Genesio–Tesi systems using the adaptive sliding mode fractional-order controller. J. Control Autom. Electr. Syst. 29(1), 15–21 (2018)

    Article  Google Scholar 

  51. Velmurugan, G., Rakkiyappan, R., Cao, J.: Finite-time synchronization of fractional-order memristor-based neural networks with time delays. Neural Netw. 73, 36–46 (2016)

    Article  MATH  Google Scholar 

  52. Wang, J., Zhou, B., Zhou, S.: An improved cuckoo search optimization algorithm for the problem of chaotic systems parameter estimation. Comput. Intell. Neurosci. 1–8, 2016 (2016)

    Google Scholar 

  53. Wang, L., Xu, Y.: An effective hybrid biogeography-based optimization algorithm for parameter estimation of chaotic systems. Expert Syst. Appl. 38(12), 15103–15109 (2011)

    Article  MathSciNet  Google Scholar 

  54. Wolpert, D.H., Macready, W.G.: No free lunch theorems for optimization. IEEE Trans. Evolut. Comput. 1(1), 67–82 (1997)

    Article  Google Scholar 

  55. Xu, S., Wang, Y., Liu, X.: Parameter estimation for chaotic systems via a hybrid flower pollination algorithm. Neural Comput. Appl. 30(8), 2607–2623 (2018)

    Article  Google Scholar 

  56. Yang, X.-S.: Flower pollination algorithm for global optimization. In: Durand-Lose, J., Jonoska, N. (eds.) Unconventional Computation and Natural Computation, pp. 240–249. Springer, Berlin, Heidelberg (2012)

    Chapter  Google Scholar 

  57. Yousri, D., AbdelAty, A.M., Said, L.A., AboBakr, A., Radwan, A.G.: Biological inspired optimization algorithms for cole-impedance parameters identification. AEU Int. J. Electron. Commun. 78, 79–89 (2017)

    Article  Google Scholar 

  58. Yousri, D., Allam, D., Eteiba, M.: Chapter 18 - parameters identification of fractional order permanent magnet synchronous motor models using chaotic meta-heuristic algorithms. In: Azar, A.T., Radwan, A.G., Vaidyanathan, S. (eds.) Mathematical Techniques of Fractional Order Systems, Advances in Nonlinear Dynamics and Chaos (ANDC), pp. 529–558. Elsevier, Amsterdam (2018)

    Chapter  Google Scholar 

  59. Zhang, K., Li, D.: Electromagnetic Theory for Microwaves and Optoelectronics. Springer, New York (2013)

    Google Scholar 

  60. Zhang, X., Liu, Z., Miao, Q., Wang, L.: Bearing fault diagnosis using a whale optimization algorithm-optimized orthogonal matching pursuit with a combined time-frequency atom dictionary. Mech. Syst. Signal Process. 107, 29–42 (2018)

    Article  Google Scholar 

  61. Zhou, P., Bai, R.-J., Zheng, J.-M.: Stabilization of a fractional-order chaotic brushless dc motor via a single input. Nonlinear Dyn. 82(1), 519–525 (2015)

    Article  MATH  Google Scholar 

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Correspondence to Lobna A. Said.

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Yousri, D.A., AbdelAty, A.M., Said, L.A. et al. Parameter identification of fractional-order chaotic systems using different Meta-heuristic Optimization Algorithms. Nonlinear Dyn 95, 2491–2542 (2019). https://doi.org/10.1007/s11071-018-4703-2

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