Abstract and Applied Analysis

Volume 2013 (2013), Article ID 461970, 7 pages

http://dx.doi.org/10.1155/2013/461970

Research Article

The Bernstein Operational Matrices for Solving the Fractional Quadratic Riccati Differential Equations with the Riemann-Liouville Derivative

Dumitru Baleanu,1,2,3 Mohsen Alipour,⁴ and Hossein Jafari⁵

¹Department of Mathematics, Cankaya University, Ogretmenler Cad. 14, Balgat, 06530 Ankara, Turkey

²Institute of Space Sciences, P.O. Box MG 23, Magurele, 077125 Bucharest, Romania

³Department of Chemical and Materials Engineering, Faculty of Engineering, King Abdulaziz University, P.O. Box 80204, Jeddah 21589, Saudi Arabia

⁴Faculty of Basic Science, Babol University of Technology, P.O. Box 47148-71167, Babol, Iran

⁵Department of Mathematics, University of Mazandaran, P.O. Box 47416-95447, Babolsar, Iran

Received 6 April 2013; Accepted 22 May 2013

Academic Editor: Ali H. Bhrawy

Copyright © 2013 Dumitru Baleanu et al. 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.

Abstract.

We obtain the approximate analytical solution for the fractional quadratic Riccati differential equation with the Riemann-Liouville derivative by using the Bernstein polynomials (BPs) operational matrices. In this method, we use the operational matrix for fractional integration in the Riemann-Liouville sense. Then by using this matrix and operational matrix of product, we reduce the problem to a system of algebraic equations that can be solved easily. The efficiency and accuracy of the proposed method are illustrated by several examples.

1. Introduction

The Riccati differential equation is named after the Italian Nobleman Count Jacopo Francesco Riccati (1676–1754). The book of Reid [1] contains the fundamental theories of the Riccati equation, with applications to random processes, optimal control, and diffusion problems. Moreover, it is well known that the one-dimensional static Schrödinger equation is closely related to a Riccati differential equation [2]. Solitary wave solution of a nonlinear partial differential equation can be represented as a polynomial in two elementary functions satisfying a projective Riccati equation [3].

In this paper, we are dealing with the fractional quadratic Riccati differential equation as follows:

subject to the initial conditions

where    = are constants and , , and are known functions. We can see [4] to guarantee the existence and uniqueness of the solution of (1) with initial conditions (2).

The general response expression (1) contains a parameter , the order of the fractional derivative that can be varied to obtain various responses. In the case that is integer, then (1) is reduced to the classical Riccati differential equation.

This problem to develop the analytical and numerical method to solve the Riccati differential equation with standard derivative, the Caputo fractional derivative and the Riemann-Liouville fractional derivative, has attracted much attention and has been studied by many authors [5–18].

The aim of this work is using the Bernstein polynomials for solving the problem (1) and (2). We notice that the problem presented [18] was in the Caputo sense but in our work, the problem is with the Riemann-Liouville derivative; therefore we considered a more general space of functions. Also, in [18], the authors used the polynomials in the form of =    = that is different from the standard Bernstein polynomials. So, the operational matrices in this work are different from those in [18].

The organization of this paper is as follows. In Section 2, the Bernstein polynomials are introduced. Some basic definitions and properties of the fractional calculus and also the BPs operational matrix for the Riemann-Liouville fractional integration are presented in Section 3. In Section 4, by BPs operational matrices, we solve the fractional quadratic Riccati differential equation. In Section 5, we discuss the convergence of the proposed method. In Section 6, several examples are considered to evaluate the power and effectiveness of the presented method. Some conclusions are summarized in the last section.

2. The Bernstein Polynomials and Their Properties

On the interval we define the Bernstein polynomials (BPs) of mth degree as follows [19]:

Set in the Hilbert space is a complete basis. We can write , where is a matrix upper triangular, , and [20].

As a result, any polynomial of degree can be expanded in terms of linear combination of    as given below:

where

The approximation of functions within the Bernstein polynomials and convergence analysis can be found in [20, 21].

3. BPs Operational Matrix for the Riemann-Liouville Fractional Integration

In this section, firstly, we give some basic definitions and properties of the fractional calculus which are used further in this paper.

Definition 1 (see [4, 22–24]). Let ; the operator , defined on by

is called the Riemann-Liouville fractional integral operator of order .

Definition 2 (see [4, 22–24]). Let and ; the operator , defined by

is called the Riemann-Liouville fractional derivative operator of order .

Definition 3 (see [4, 22–24]). Let , , and . The operator , defined by

is called the Caputo fractional derivative operator of order .

Lemma 4. If , , and , then

Proof. See [22–24].

Theorem 5. One can get BPs operational matrix from order for the Riemann-Liouville fractional integral as

Proof. See [21].

4. BPs for Solving the Fractional Quadratic Riccati Differential Equation

Firstly, we use the initial conditions to reduce a given initial-value problem to a problem with zero initial conditions.

So, we define

where is some known function that satisfied the initial conditions (2) and is a new unknown function.

Substituting (13) in (1) and (2), we have an initial-value problem as follows:

subject to the initial conditions

On the other hand, by (11) in Lemma 4 we can write

Also, by using Lemma 3.3 in [20] the inputs , , , and can be approximated as follows:

where , , and are known column vectors and is an unknown column vector.

From (10), (15), (16), (18), and (12), we have

where .

Now, by substituting (17)–(21) into (14), we obtain

Then, from Lemma  3.5 in [20] we have

Therefore we can reduce (22) by (23)–(25) as

Finally, we obtain the following nonlinear system of algebraic equation:

such that by solving this system we can obtain the vector . Then, we can get

5. Convergence Analysis

In this section, we investigate the convergence analysis for the method presented in Section 4.

The problem (14) changes to the following problems

since

By taking we obtain the following fractional integral equation:

If we use the approximation , then the problem (31) from space reduces to the following problem in space :

Now, similar to Theorem  6.1 in [21], we propose the next theorem.

Theorem 6. Suppose that is the exact solution of (31) and , where

Then one has as (i.e.,   as ).

Proof. By substituting (33) instead of in [21], we can use the proof of Theorem  6.1 in [21].

Theorem 7. Suppose that is the exact solution of (31) and is the obtained solution of (26). Then one has as.

Proof. Substituting (17), (19), (20), and (12) in (32) we have

From Lemmas 2.3 and  4.1 in [21], we have as . So we can observe that as increases, (34) gets close to (32). Now, by taking we propose the following problem that gets close to (32) as increases:

Then by (23) and (25), (35) reduces to the following equation:

Equation (36) gets to (35) as , because from Lemma  3.1 in [21] as . Then by deleting , , taking , and using (24) in (36), we have

where, from Lemma  3.1 in [21], as . Now, by taking and deleting in (37), we get (26). Obviously, if is solution of (32), then we have    as .

On the other hand, from Theorem 6 we obtained as . Therefore we can write as and the proof is complete.

6. Illustrative Numerical Examples

In this section, we apply our method with (BPs of degree ) to solve the following examples. We define and for the approximate solution and the exact solution, respectively.

Example 1. Consider the nonlinear Riccati differential equation [14]:

subject to the initial condition as . The exact solution of the equation for is given as

Numerical results compared to [14] are given in Table 1 and also Figure 1 shows the absolute error for our method for and Figure 2 shows behavior for different values of .

Table 1: Numerical results for and in Example 1 with comparison to exact solution and [14].

Exact
Present method

Reference [14]

0.1
0.099668
0.099668
0.099668

0.2
0.197375
0.197375
0.197375

0.3
0.291313
0.291313
0.291313

0.4
0.379949
0.379949
0.379944

0.5
0.462117
0.462117
0.462078

0.6
0.537050
0.537050
0.536857

0.7
0.604368
0.604368
0.603631

0.8
0.664037
0.664037
0.661706

0.9
0.716298
0.716298
0.709919

1
0.761594
0.761594
0.746032

Figure 1: Behavior of the absolute error function in Example 1 for and .

Figure 2: Behavior of in Example 1 for different and exact solution for .

Example 2. Consider the following quadratic Riccati differential equation of fractional order [14]

subject to the initial condition as . The exact solution of the equation for is given as

Numerical results compared to [14] are given in Table 2 and also, Figure 3 shows the absolute error for our method for and Figure 4 shows behavior for different values of .

Table 2: Numerical results for and in Example 2 with comparison to exact solution and [14].

Exact
Present method

Reference [14]

0.1
0.110295
0.110295
0.110294

0.2
0.241977
0.241977
0.241965

0.3
0.395105
0.395105
0.395106

0.4
0.567812
0.567812
0.568115

0.5
0.756014
0.756014
0.757564

0.6
0.953566
0.953566
0.958259

0.7
1.152949
1.152949
1.163459

0.8
1.346364
1.346364
1.365240

0.9
1.526911
1.526911
1.554960

1
1.689499
1.689499
1.723810

Figure 3: Behavior of the absolute error function in Example 2 for and .

Figure 4: Behavior of in Example 2 for different and exact solution for .

Example 3. Consider the nonlinear fractional differential equation:

with the initial conditions

This problem has been studied by using ADM [25], FDTM [26], and BPFs [27]. Our results with , are compared to [25–27] in Tables 3 and 4. Therefore, we see that our method is very effective and obtained solutions that are in good agreement with the results in [25–27]. Also, Figure 5 shows behavior for different values of .

Table 3: Numerical results for in Example 3 with comparison to [25–27].

Present method

ADM [25]
FDTM [26]
BPFs [27]

0.1
0.023779
0.023790
0.023790
0.023800

0.2
0.067336
0.067330
0.067330
0.067335

0.3
0.123886
0.123896
0.123896
0.123900

0.4
0.191373
0.191362
0.191362
0.191368

0.5
0.268851
0.268856
0.268856
0.268862

0.6
0.356235
0.356238
0.356238
0.356244

0.7
0.453958
0.453950
0.453950
0.453956

0.8
0.562999
0.563007
0.563007
0.563014

0.9
0.685066
0.685056
0.685056
0.685067

1
0.822540
0.822511
0.822509
0.822525

Table 4: Numerical results for in Example 3 with comparison to [25, 26].

Present method

ADM [25]
FDTM [26]

0.1
0.000952
0.000952
0.000952

0.2
0.005383
0.005383
0.005383

0.3
0.014833
0.014833
0.014833

0.4
0.030450
0.030450
0.030450

0.5
0.053197
0.053197
0.053197

0.6
0.083925
0.083925
0.083925

0.7
0.123412
0.123412
0.123412

0.8
0.172391
0.172391
0.172391

0.9
0.231574
0.231574
0.231574

1
0.301676
0.301676
0.301676

Figure 5: Plot of for different in Example 3.

7. Conclusion

In this paper, we proposed a numerical method for solving the fractional quadratic Riccati differential equations by the operational matrices of the Bernstein polynomials. We applied operational matrix for fractional integration in the Riemann-Liouville sense. Then by using this matrix and operational matrix of product, we reduced the fractional quadratic Riccati differential equation to a system of algebraic equations that can be solved easily. Finally, examples have been simulated to demonstrate the high performance of the proposed method. We saw that the results were in good agreement with the analytical solutions and the solutions in the open literatures. Also, we observed that the solutions approach to classical solutions as the order of the fractional derivatives approaches 1, for fixed .

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