Complexity

Complexity / 2020 / Article

Research Article | Open Access

Volume 2020 |Article ID 1010382 | https://doi.org/10.1155/2020/1010382

Ayed Al e’damat, "Approximate Analytical Solution for a Coupled System of Fractional Nonlinear Integrodifferential Equations by the RPS Method", Complexity, vol. 2020, Article ID 1010382, 8 pages, 2020. https://doi.org/10.1155/2020/1010382

Approximate Analytical Solution for a Coupled System of Fractional Nonlinear Integrodifferential Equations by the RPS Method

Academic Editor: Honglei Xu
Received03 Feb 2020
Accepted18 Jul 2020
Published13 Aug 2020

Abstract

In this work, a modified residual power series method is implemented for providing efficient analytical and approximate solutions for a class of coupled system of nonlinear fractional integrodifferential equations. The proposed algorithm is based on the concept of residual error functions and generalized power series formula. The fractional derivative is described under the Caputo concept. To illustrate the potential, accuracy, and efficiency of the proposed method, two numerical applications of the coupled system of nonlinear fractional integrodifferential equations are tested. The numerical results confirm the theoretical predictions and depict that the suggested scheme is highly convenient, is quite effective, and practically simplifies computational time. Consequently, the proposed method is simple, accurate, and convenient in handling different types of fractional models arising in the engineering and physical systems.

1. Introduction

The theory of fractional calculus is indeed a generalization of the standard calculus that deals with differentiation and integration of a noninteger order, which is utilized to describe various real-world phenomena arising in natural sciences, applied mathematics, and engineering fields with great applications for these tools, including nonlinear oscillation of earthquakes, fractional fluid-dynamic traffic, economics, solid mechanics, viscoelasticity, and control theory [17]. The major cause behind this is that modeling of a specific phenomenon does not depend only at the time instant but also the historical state, so the differential and integral operators for integer and fractional cases are found to be a superb tool in describing the hereditary and memory properties for different engineering and physical phenomena [812]. However, several mathematical forms of the abovementioned issues contain nonlinear fractional integrodifferential equations (FIDEs), and other nonlinear models can be found in [1318]. Since most fractional differential and integrodifferential equations cannot be solved analytically, it is necessary to find an accurate numerical and analytical method to deal with the complexity of fractional operators involving such equations [1924].

This paper aims to introduce a recent analytical as well as numerical method based on the use of fractional residual power series (RPS) technique for obtaining the approximate solution for a class of coupled system of fractional integrodifferential equations in the following form:

This is subject to the following initial conditions:where .

The residual power series method (RPSM) has a wide range of applications, especially in simulating nonlinear issues in a fractional meaning, which has been developed and modified over recent years as a powerful mathematical treatment indispensable in dealing with the emerging realistic system in physics, engineering, and natural sciences [2528]. More specifically, it is a modern analytical and approximation technique that relies on the expansion of the fractional power series and residual error functions, which was first proposed in 2013 to provide analytical series solutions to fuzzy differential equations of the first and second orders and minimize the residual errors. This method has many advantages and properties as follows: it is an accurate alternative instrument, it requires less effort to achieve results, it provides a rapid convergence rate to the exact solution, it deals directly with different types of nonlinear terms and complex functions, and it has the ability to choose any point in the integration domain, making the approximate solution applicable. It has also excellent estimating characteristics that reflect high reliability. Furthermore, it is a systematic tool to find sequential solutions for several types of nonlinear differential equations and integrodifferential equations of fractional order without having to discretize, linearize, or even expose to perturbation. Therefore, it attracted the attention of many researchers.

Freihet et al. [29] have used the fractional power series for solving the fractional stiff system and introduced some basic theorems related to RPS generalization in the sense of Caputo fractional derivative. The (2 + 1)-dimensional time-fractional Burgers–Kadomtsev–Petviashvili equation has been solved by the RPS method [30]. In [31], analytic-approximate solutions for nonlinear coupled fractional Jaulent–Miodek equations with energy-dependent Schrödinger potential have been obtained using the RPS and q-homotopy analysis methods. Moreover, this method was successfully applied for solving both linear and nonlinear ordinary, partial, and fuzzy differential equations [3237]. Therefore, such adaptives can be used as an alternative technique in solving several nonlinear problems arising in engineering and sciences.

The outline of this paper is organized as follows: In the next section, we review some basic definitions and theories related to fractional differentiation and fractional power series representations. In Section 3, the solution by the RPS technique is provided. In Section 4, numerical application is performed to show accuracy and efficiency of the RPS method. Finally, we give concluding remarks in Section 5.

2. Basic Mathematical Concepts

In this section, basic definitions and results related to fractional calculus are given and fractional power series concept is also represented.

Definition 1. The Riemann–Liouville fractional integral operator of order , over the interval for a function , is defined byFor and , the operator has the following basic properties:(1)(2)(3)

Definition 2. For . The Caputo fractional derivative of order is given byFor In case and then .
The following are some interesting properties of the operator :(1)For any constant , then .(2)(3)(4)

Definition 3. A fractional power series (FPS) representation at has the following form:where and and is the coefficient of the series.

Theorem 1. Suppose that has the following FPS representation at :where , and for . Then, the coefficients will be in the form such that (-times).

3. Fractional RPS Method for the Coupled System of IDEs

The purpose of this section is to construct FPS solution for the coupled system of nonlinear fractional integrodifferential equations (1) and (2) by substituting the FPS expansion among the truncated residual functions.

The RPS algorithm proposing the solution of equations (1) and (2) about gives the following FPS expansion:

The truncated series form of equation (7) can be given by the following th-FPS approximate solution:

Clearly, if , then expansion (8) can be written as

Define the residual function for equations (1) and (2) as follows:

Also, define the th-residual function as

According to the RPS algorithm [2732], we have the following relations:(i), for each (ii), for each

For obtaining the coefficients , , one can solve the solution of the following relation:

Algorithm 1. To find the coefficients in equation (9), perform the following steps:(i)Step 1: substitute expansion (9) function , into -th residual function (11) such that (ii)Step 2: find the relation of fractional formula of at (iii)Step 3: for obtain the relation through the fact . For obtain the relation through the fact . For obtain the relation through the fact , obtain the relation through the fact (iv)Step 4: solve the obtained algebraic fractional system (v)Step 5: substitute the values of back into equation (8) and then stop.

4. Numerical Applications and Simulation

This section aims to test two applications of the system of nonlinear fractional IDEs to show the efficiency, accuracy, and applicability of the proposed method. In this section, all calculations are preformed using Wolfram-Mathematica 10.

Example 1. Consider the following nonlinear fractional integrodifferential equation:This is subject to the following initial conditions:The exact solution of this coupled system is and .
Using the RPS algorithm, the -th residual functions are given bywhere has the following form:Consequently,Numerical simulation specializes in advanced numeric or approximate methods for finding digital or approximate solutions and estimating errors of these approximations. For such purpose, a few decimal numbers are often recorded to calculate the absolute error, which produces some vague estimates related to significance and units, as well as does not provide clear and explicit evidence regarding the subject matter of the study. Therefore, the comparison of absolute error with the exact value leads to the determination of the relative error as a ratio between the value of absolute error and the exact, which gives some importance and reduces ambiguity for a deeper understanding of the behavior of the approximate solutions. By using the RPS method of Example 1, the numerical results of and are shown in Tables 1 and 2 at and The results obtained in Tables 1 and 2 show that the error estimate using the proposed method is very small and that the solutions correspond well to each other. In general, it should be noted that increasing the number of iterations will lead to an improvement in numerical solutions and approaching the exact value.
Tables 3 and 4 show the sixth approximate solutions of Example 1 at different values of such that with step size and . From these tables, it can be concluded that the RPS algorithm and the approximate solutions are consistent with each other and with the exact solutions for all values of in . Here, it is worth noting that the closer the value of the fractional derivative approaching the integer case , the closer the approximate solution is to the exact solution.



01.01.00.0
0.11.10517091.1051708
0.21.22140281.2214000
0.31.34985881.3498375
0.41.49182471.4917333
0.51.64872131.6484375
0.61.82211881.8214000
0.72.01375272.0121708
0.82.22554092.2224000
0.92.45960312.4538375
1.02.71828182.7083333



01.01.00.0
0.10.90483740.9048375
0.20.81873080.8187333
0.30.74081820.7408375
0.40.670332010.6704000
0.50.60653070.6067708
0.60.54881160.5494000
0.70.49658530.4978375
0.80.44932900.4517333
0.90.40656970.4108375
1.00.36787940.3750000



0.01.01.01.01.0
0.11.05108331.07339611.10738841.1601510
0.21.12466671.17168231.23921291.3365098
0.31.22125001.29563811.39742291.5359285
0.41.34133331.44461541.58015781.7560644
0.51.48541671.61817481.78607761.9951767
0.61.65400001.81603452.01420212.2519736
0.71.84758332.03802172.26378742.5254605
0.82.06666672.28404012.53425262.8148458
0.92.31175002.55404952.82513333.1194830
1.02.58333332.84805183.13605143.4388329



0.01.01.01.01.0
0.10.90483330.87807790.84606940.8088467
0.20.81866660.78554780.74993950.7123611
0.30.74049990.70717360.67345200.6391004
0.40.66933330.63862100.60841740.5772768
0.50.60416660.57720550.55052850.5214466
0.60.54399990.52091630.49696430.4684158
0.70.48783330.46810270.44565630.4160595
0.80.43466660.41733750.39498000.3628482
0.90.38350000.36734490.34359910.3076204
1.00.33333330.31695920.29037840.2494581

Example 2. Consider the following fractional integrodifferential equation:This is subject to the following initial conditions:The exact solution of this coupled system is and . Using the RPS algorithm, the -th residual functions and are given bywhere and have the following form:The absolute errors are listed in Tables 5 and 6. The results obtained by the RPS method show that the exact solutions are in good agreement with approximate solutions at , , and step size . Tables 7 and 8 show approximate solutions at different values of such that and with step size . From these tables, one can find that the RPS method provides us with an accurate approximate solution, which is in good agreement with the exact solutions for all values of in . Also, it is worth noting that the closer the value of the fractional derivative approaching the integer case , the closer the approximate solution is to the exact solution.



0.10.09983340.0998257
0.20.19866930.1986624
0.30.29552020.2955216
0.40.38941830.3894152
0.50.47942550.4794232
0.60.56464250.5646492
0.70.64421770.6442199
0.80.71735610.7173533
0.90.78332690.7833286
1.00.84147100.8414475



0.10.99500420.9950103
0.20.98006660.9800597
0.30.95533650.9553270
0.40.92106100.9210410
0.50.87758260.8775771
0.60.82533560.8253269
0.70.76484220.7645622
0.80.69670670.6966984
0.90.62161000.6215986
1.00.54030230.5402669



0.00.00.00.0
0.10.07495010.10278650.1422048
0.20.15536180.20210550.2644892
0.30.24514620.30866290.3897369
0.40.34455770.42310600.5195960
0.50.45358020.54543020.6544017
0.60.57214340.67549410.7941689
0.70.70016950.81312910.9388129
0.80.83758540.95816931.0882176
0.90.98432691.11046091.2422602
1.01.14033821.26986351.4008207



0.01.01.01.0
0.11.00368390.99957980.9902709
0.20.99181770.97706930.9526430
0.30.96781310.94094530.9018037
0.40.93296890.89384120.8413882
0.50.88811390.83727770.7733064
0.60.83385920.77229220.6987749
0.70.77069010.69965780.6186510
0.80.69901080.61998320.5335787
0.90.61916850.53376640.4440635
1.00.53146840.44142620.3505153

5. Concluding Remarks

In this work, a class of a coupled system of nonlinear fractional integrodifferential equations of fractional order has been discussed by using the RPS method under the Caputo fractional derivative. The RPS algorithm has been given to optimize the approximate solution by minimizing a residual error function with the help of generalized Taylor formula. To demonstrate the consistency with the theoretical framework, two illustrative examples have been provided. The obtained results indicated that the approximate solutions are coinciding with the exact solution and with each other for different values of the fractional order over the selected nods and parameters. From our results, we can conclude that the RPS method is a systematic and suitable scheme to address many fractional initial value problems with great potential in scientific applications. The calculations have been performed by using Wolfram-Mathematica 10.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The author declares that there are no conflicts of interest.

References

  1. Y. A. Rossikhin and M. V. Shitikova, “Applications of fractional calculus to dynamic problems of linear and nonlinear hereditary mechanics of solids,” Applied Mechanics Reviews, vol. 50, no. 1, pp. 15–67, 1997. View at: Publisher Site | Google Scholar
  2. R. T. Baillie, “Long memory processes and fractional integration in econometrics,” Journal of Econometrics, vol. 73, no. 1, pp. 5–59, 1996. View at: Publisher Site | Google Scholar
  3. K. S. Miller and B. Ross, An Introduction to the Fractional Calculus and Fractional Differential Equations, John Wiley and Sons, Hoboken, NY, USA, 1993.
  4. X.-J. Yang, General Fractional Derivatives: Theory, Methods and Applications, CRC Press, New York, NY, USA, 2019.
  5. X.-J. Yang, F. Gao, and Y. Ju, General Fractional Derivatives with Applications in Viscoelasticity, Academic Press, Cambridge, MA, USA, 2020.
  6. X. J. J. A. T. Yang and J. A. Tenreiro Machado, “A new fractal nonlinear Burgers’ equation arising in the acoustic signals propagation,” Mathematical Methods in the Applied Sciences, vol. 42, no. 18, pp. 7539–7544, 2019. View at: Publisher Site | Google Scholar
  7. L. Akinyemi and O. S. Iyiola, “A reliable technique to study nonlinear time-fractional coupled Korteweg-de Vries equations,” Advances in Difference Equations, vol. 2020, no. 1, Article ID 169, 27 pages, 2020. View at: Publisher Site | Google Scholar
  8. M. Al-Smadi, “Simplified iterative reproducing kernel method for handling time-fractional BVPs with error estimation,” Ain Shams Engineering Journal, vol. 9, no. 4, pp. 2517–2525, 2018. View at: Publisher Site | Google Scholar
  9. S. Momani, A. Freihat, and M. Al-Smadi, “Analytical study of fractional-order multiple chaotic Fitzhugh-Nagumo neurons model using multistep generalized differential transform method,” Abstract and Applied Analysis, vol. 2014, Article ID 276279, 10 pages, 2014. View at: Publisher Site | Google Scholar
  10. Z. Altawallbeh, M. Al-Smadi, I. Komashynska, and A. Ateiwi, “Numerical solutions of fractional systems of two-point BVPs by using the iterative reproducing kernel algorithm,” Ukrainian Mathematical Journal, vol. 70, no. 5, pp. 687–701, 2018. View at: Publisher Site | Google Scholar
  11. O. Abu Arqub and M. Al-Smadi, “An adaptive numerical approach for the solutions of fractional advection-diffusion and dispersion equations in singular case under Riesz’s derivative operator,” Physica A: Statistical Mechanics and Its Applications, vol. 540, Article ID 123257, 13 pages, 2020. View at: Publisher Site | Google Scholar
  12. M. Al-Smadi and O. A. Arqub, “Computational algorithm for solving fredholm time-fractional partial integrodifferential equations of dirichlet functions type with error estimates,” Applied Mathematics and Computation, vol. 342, pp. 280–294, 2019. View at: Publisher Site | Google Scholar
  13. M. Al-Smadi, “Solving fractional system of partial differential equations with parameters derivative by combining the GDTM and RDTM,” Nonlinear Studies, vol. 26, no. 3, pp. 587–601, 2019. View at: Google Scholar
  14. M. Al-Smadi, O. Abu Arqub, and S. Momani, “A computational method for two-point boundary value problems of fourth-order mixed integrodifferential equations,” Mathematical Problems in Engineering, vol. 2013, Article ID 832074, 10 pages, 2013. View at: Publisher Site | Google Scholar
  15. D. Zeidan, A. Slaouti, E. Romenski, and E. F. Toro, “Numerical solution for hyperbolic conservative two-phase flow equations,” International Journal of Computational Methods, vol. 4, no. 2, pp. 299–333, 2017. View at: Publisher Site | Google Scholar
  16. M. Al-Smadi, “Reliable Numerical algorithm for handling fuzzy integral equations of second kind in Hilbert spaces,” Filomat, vol. 33, no. 2, pp. 583–597, 2019. View at: Publisher Site | Google Scholar
  17. G. N. Gumah, M. F. M. Naser, M. Al-Smadi, and S. K. Al-Omari, “Application of reproducing kernel Hilbert space method for solving second-order fuzzy Volterra integro-differential equations,” Advances in Difference Equations, vol. 2018, no. 1, Article ID 457, 15 pages, 2018. View at: Publisher Site | Google Scholar
  18. M. Al-Smadi, A. Freihat, O. Abu Arqub, and N. Shawagfeh, “A novel multistep generalized differential transform method for solving fractional-order Lü chaotic and hyperchaotic systems,” Journal of Computational Analysis and Applications, vol. 19, no. 4, pp. 713–724, 2015. View at: Google Scholar
  19. M. Al-Smadi, O. A. Arqub, N. Shawagfeh, and S. Momani, “Numerical investigations for systems of second-order periodic boundary value problems using reproducing kernel method,” Applied Mathematics and Computation, vol. 291, pp. 137–148, 2016. View at: Publisher Site | Google Scholar
  20. E. Goncalvès and D. Zeidan, “Numerical simulation of unsteady cavitation in liquid hydrogen flows,” International Journal of Engineering Systems Modelling and Simulation, vol. 9, no. 1, pp. 41–51, 2017. View at: Publisher Site | Google Scholar
  21. G. Gumah, M. F. M. Naser, M. Al-Smadi, S. K. Q. Al-Omari, and D. Baleanu, “Numerical solutions of hybrid fuzzy differential equations in a hilbert space,” Applied Numerical Mathematics, vol. 151, pp. 402–412, 2020. View at: Publisher Site | Google Scholar
  22. M. Al-Smadi, A. Freihat, H. Khalil, S. Momani, and R. A. Khan, “Numerical multistep approach for solving fractional partial differential equations,” International Journal of Computational Methods, vol. 14, no. 2, Article ID 1750029, 15 pages, 2017. View at: Publisher Site | Google Scholar
  23. M. H. AL-Smadi and G. N. Gumah, “On the homotopy analysis method for fractional SEIR epidemic model,” Research Journal of Applied Sciences, Engineering and Technology, vol. 7, no. 18, pp. 3809–3820, 2014. View at: Publisher Site | Google Scholar
  24. I. Komashynska and M. Al-Smadi, “Iterative reproducing kernel method for solving second-order integrodifferential equations of fredholm type,” Journal of Applied Mathematics, vol. 2014, Article ID 459509, 11 pages, 2014. View at: Publisher Site | Google Scholar
  25. I. Komashynska, M. Al-Smadi, O. Abu Arqub, and S. Momani, “An efficient analytical method for solving singular initial value problems of nonlinear systems,” Applied Mathematics & Information Sciences, vol. 10, no. 2, pp. 647–656, 2016. View at: Publisher Site | Google Scholar
  26. A. El-Ajou, M. Al-Smadi, M. a. N. Oqielat, S. Momani, and S. Hadid, “Smooth expansion to solve high-order linear conformable fractional PDEs via residual power series method: applications to physical and engineering equations,” Ain Shams Engineering Journal, 2020, In Press. View at: Publisher Site | Google Scholar
  27. I. Komashynska, M. Al-Smadi, A. Ateiwi, and S. Al-Obaidy, “Approximate analytical solution by residual power series method for system of Fredholm integral equations,” Applied Mathematics & Information Sciences, vol. 10, no. 3, pp. 975–985, 2016. View at: Publisher Site | Google Scholar
  28. M. Al-Smadi, O. Abu Arqub, and S. Momani, “Numerical computations of coupled fractional resonant Schrödinger equations arising in quantum mechanics under conformable fractional derivative sense,” Physica Scripta, vol. 95, no. 7, Article ID 075218, 2020. View at: Publisher Site | Google Scholar
  29. A. Freihet, S. Hasan, M. Al-Smadi, M. Gaith, and S. Momani, “Construction of fractional power series solutions to fractional stiff system using residual functions algorithm,” Advances in Difference Equations, vol. 95, 2019. View at: Publisher Site | Google Scholar
  30. M. Senol, “Analytical and approximate solutions of (2 + 1)-dimensional time-fractional Burgers-Kadomtsev-Petviashvili equation,” Communications in Theoretical Physics, vol. 72, no. 5, Article ID 055003, 2020. View at: Publisher Site | Google Scholar
  31. M. Şenol, O. S. Iyiola, H. D. Kasmaei, and L. Akinyemi, “Efficient analytical techniques for solving time-fractional nonlinear coupled Jaulent–Miodek system with energy-dependent Schrödinger potential,” Advances in Difference Equations, vol. 2019, Article ID 459509, 11 pages, 2019. View at: Publisher Site | Google Scholar
  32. M. Al-Smadi, O. Abu Arqub, and S. Hadid, “An attractive analytical technique for coupled system of fractional partial differential equations in shallow water waves with conformable derivative,” Communications in Theoretical Physics, vol. 72, no. 8, Article ID 085001, 2020. View at: Publisher Site | Google Scholar
  33. S. Hasan, M. Al-Smadi, A. Freihet, and S. Momani, “Two computational approaches for solving a fractional obstacle system in Hilbert space,” Advances in Difference Equations, vol. 2019, no. 1, Article ID 55, 17 pages, 2019. View at: Publisher Site | Google Scholar
  34. R. Saadeh, M. Alaroud, M. Al-Smadi, R. Ahmad, and U. Salma Din, “Application of fractional residual power series algorithm to solve newell-whitehead-segel equation of fractional order,” Symmetry, vol. 11, no. 12, p. 1431, 2019. View at: Publisher Site | Google Scholar
  35. A. Freihet, H. Shatha, M. Alaroud, M. Al-Smadi, R. R. Ahmad, and U. K. Salma Din, “Toward computational algorithm for time-fractional Fokker–Planck models,” Advances in Mechanical Engineering, vol. 11, no. 10, pp. 1–11, 2019. View at: Publisher Site | Google Scholar
  36. S. Alshammari, M. Al-Smadi, M. Al Shammari, I. Hashim, and M. A. Alias, “Advanced analytical treatment of fractional logistic equations based on residual error functions,” International Journal of Differential Equations, vol. 2019, Article ID 7609879, pp. 1–11, 2019. View at: Publisher Site | Google Scholar
  37. S. Alshammari, M. Al-Smadi, I. Hashim, and M. A. Alias, “Residual power series technique for simulating fractional Bagley-Torvik problems emerging in applied physics,” Applied Sciences, vol. 9, no. 23, p. 5029, 2019. View at: Publisher Site | Google Scholar

Copyright © 2020 Ayed Al e’damat. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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