Abstract

A numerical method to solve nonlinear Fredholm integral equations of second kind is presented in this work. The method is based upon hybrid function approximate. The properties of hybrid of block-pulse functions and Taylor series are presented and are utilized to reduce the computation of nonlinear Fredholm integral equations to a system of algebraic equations. Some numerical examples are selected to illustrate the effectiveness and simplicity of the method.

1. Introduction

Over the last years, the fractional calculus has been used increasingly in different areas of applied science. This tendency could be explained by the deduction of knowledge models which describe real physical phenomena. In fact, the fractional derivative has been proved reliable to emphasize the long memory character in some physical domains especially with the diffusion principle. For example, the nonlinear oscillation of earthquake can be modeled with fractional derivatives, and the fluid-dynamic traffic model with fractional derivatives can eliminate the deficiency arising from the assumption of continuum traffic flow [1]. In the fields of physics and chemistry, fractional derivatives and integrals are presently associated with the application of fractals in the modeling of electrochemical reactions, irreversibility and electromagnetism [2], heat conduction in materials with memory, and radiation problems. Many mathematical formulations of mentioned phenomena contain nonlinear integrodifferential equations with fractional order. Nonlinear phenomena are also of fundamental importance in various fields of science and engineering. The nonlinear models of real-life problems are still difficult to be solved either numerically or theoretically. There has recently been much attention devoted to the search for better and more efficient solution methods for determining a solution, approximate or exact, analytical or numerical, to nonlinear models [3, 4].

In this paper, we study the numerical solution of a nonlinear fractional integro-differential equation of the second kind:𝐷𝛼𝑓(𝑥)𝜆10[]𝑘(𝑥,𝑡)𝑓(𝑡)𝑞𝑑𝑡=𝑔(𝑥),𝑞>1,(1.1) with the initial condition𝑓(𝑖)(0)=𝛿𝑖,𝑖=0,1,,𝑟1,𝑟1<𝛼𝑟,𝑟𝑁,(1.2) by hybrid of block-pulse functions and Taylor series. Here, 𝑔𝐿2([0,1)),𝑘𝐿2([0,1)2)is known functions, and 𝑓(𝑥)is unknown function. 𝐷𝛼is the Caputo fractional differentiation operator and 𝑞is a positive integer.

During the last decades, several methods have been used to solve fractional differential equations, fractional partial differential equations, fractional integro-differential equations and dynamic systems containing fractional derivatives, such as Adomian’s decomposition method [59], He’s variational iteration method [1012], homotopy perturbation method [13, 14], homotopy analysis method [15], collocation method [16], Galerkin method [17], and other methods [1820].

2. Basic Definitions

We give some basic definitions and properties of the fractional calculus theory which are used further in this paper.

Definition 2.1. The Riemann-Liouville fractional integral operator of order 𝛼0 is defined as [21] 𝐽𝛼1𝑓(𝑥)=Γ(𝛼)𝑥0(𝑥𝑡)𝛼1𝐽𝑓(𝑡)𝑑𝑡,𝛼>0,𝑥>0,0𝑓(𝑥)=𝑓(𝑥).(2.1) It has the following properties 𝐽𝛼𝑥𝛾=Γ(𝛾+1)𝑥Γ(𝛼+𝛾+1)𝛼+𝛾,𝛾>1.(2.2)

Definition 2.2. The Caputo definition of fractional derivative operator is given by 𝐷𝛼𝑓(𝑥)=𝐽𝑚𝛼𝐷𝑚1𝑓(𝑥)=Γ(𝑚𝛼)𝑥0(𝑥𝑡)𝑚𝛼1𝑓(𝑚)(𝑡)𝑑𝑡,(2.3) where 𝑚1<𝛼𝑚,𝑚𝑁,𝑥>0. It has the following two basic properties 𝐷𝛼𝐽𝛼𝐽𝑓(𝑥)=𝑓(𝑥),(2.4)𝛼𝐷𝛼𝑓(𝑥)=𝑓(𝑥)𝑚1𝑘=0𝑓(𝑘)0+𝑥𝑘𝑘!,𝑥>0.(2.5)

3. Properties of Hybrid Functions

3.1. Hybrid Functions of Block-Pulse and Taylor Polynomials

Hybrid functions 𝑛𝑚(𝑥),𝑛=1,2,,𝑁,𝑚=0,1,2,,𝑀1,are defined on the interval [0,1) as𝑛𝑚𝑇(𝑥)=𝑚(𝑁𝑥(𝑛1)),𝑥𝑛1𝑁,𝑛𝑁,0,otherwise,(3.1) where 𝑛 and 𝑚are the orders of block-pulse functions and Taylor polynomials, respectively and 𝑇𝑚(𝑥)=𝑥𝑚.

3.2. Function Approximation

A function 𝑦(𝑥)𝐿2[0,1) may be expanded as𝑦(𝑥)=𝑛=1𝑚=0𝑐𝑛𝑚𝑛𝑚(𝑥),(3.2) where𝑐𝑛𝑚=1𝑁𝑚𝑑𝑚!𝑚𝑦(𝑥)𝑑𝑥𝑚||||𝑥=((𝑛1)/𝑁).(3.3) If 𝑦(𝑥)in (3.2) is truncated, then (3.2) can be written as𝑦(𝑥)=𝑁𝑛=1𝑀1𝑚=0𝑐𝑛𝑚𝑛𝑚(𝑥)𝐶𝑇𝐻(𝑥)=𝐻𝑇(𝑥)𝐶,(3.4) where 𝑐𝐶=10,𝑐11,,𝑐1𝑀1,𝑐20,,𝑐2𝑀1,𝑐𝑁0,,𝑐𝑁𝑀1𝑇,(3.5)𝐻(𝑥)=10(𝑥),11(𝑥),,1𝑀1(𝑥),20(𝑥),,2𝑀1(𝑥),𝑁0(𝑥),,𝑁𝑀1(𝑥)𝑇.(3.6) In (3.5) and (3.6), 𝑐𝑛𝑚,𝑛=1,2,,𝑁,𝑚=0,1,,𝑀1,are the coefficients expansions of the function 𝑦(𝑥)in the 𝑛th subinterval [(𝑛1)/𝑁,𝑛/𝑁] and 𝑛𝑚(𝑥),𝑛=1,2,,𝑁,𝑚=0,1,,𝑀1,are defined in (3.1).

3.3. Operational Matrix of the Fractional Integration

The integration of the vector 𝐻(𝑡)defined in (3.6) can be obtained as𝑡0𝐻(𝜏)𝑑𝜏𝑃𝐻(𝑡),(3.7) see, [22], where 𝑃is the 𝑀𝑁×𝑀𝑁operational matrix for integration.

Our purpose is to derive the hybrid functions operational matrix of the fractional integration. For this purpose, we consider an 𝑚-set of block pulse function as𝑏𝑖𝑖(𝑡)=1,𝑚𝑡(𝑖+1)𝑚,0,otherwise,(3.8) where 𝑚=𝑀𝑁,𝑖=0,1,2,,(𝑚1).

The functions 𝑏𝑖(𝑡) are disjoint and orthogonal. That is,𝑏𝑖(𝑡)𝑏𝑗𝑏(𝑡)=0,𝑖𝑗,𝑖(𝑡),𝑖=𝑗.(3.9) From the orthogonality of property, it is possible to expand functions into their block pulse series.

Similarly, hybrid function may be expanded into an 𝑚-set of block pulse function as𝐻(𝑡)=Φ𝐵(𝑡),(3.10) where 𝐵(𝑡)=[𝑏1(𝑡),𝑏2(𝑡),,𝑏𝑚(𝑡)], Φ is a 𝑀𝑁×𝑀𝑁matrix.

In [23], Kilicman and Al Zhour have given the block pulse operational matrix of the fractional integration 𝐹𝛼as follows:𝐽𝑎𝐵(𝑥)𝐹𝛼𝐵(𝑥),(3.11) where𝐹𝛼=1𝑁𝑀𝛼1Γ(𝛼+2)1𝜉1𝜉2𝜉3𝜉𝑙101𝜉1𝜉2𝜉𝑙2001𝜉1𝜉𝑙30000𝜉100001,(3.12) with 𝜉𝑘=(𝑘+1)𝛼+12𝑘𝛼+1+(𝑘1)𝛼+1.

Next, we derive the hybrid function operational matrix of the fractional integration. Let𝐽𝛼𝐻(𝑥)𝑃𝛼𝐻(𝑥),(3.13) where matrix 𝑃𝛼is called the hybrid function operational matrix of fractional integration.

Using (3.10) and (3.11), we have𝐽𝛼𝐻(𝑥)𝐽𝛼Φ𝐵(𝑥)=Φ𝐽𝛼𝐵(𝑥)Φ𝐹𝛼𝐵(𝑥).(3.14) From (3.10) and (3.13), we get𝑃𝛼𝐻(𝑥)=𝑃𝛼Φ𝐵(𝑥)=Φ𝐹𝛼𝐵(𝑥).(3.15) Then, the hybrid function operational matrix of fractional integration 𝑃𝛼is given by𝑃𝛼=Φ𝐹𝛼Φ1.(3.16) Therefore, we have found the operational matrix of fractional integration for hybrid function.

3.4. The Product Operational of the Hybrid of Block-Pulse and Taylor Polynomials

The following property of the product of two hybrid function vectors will also be used.

Let 𝐻(𝑥)𝐻𝑇(𝑥)𝐶𝐶𝐵(𝑥),(3.17) see, [22], where 𝐶𝐶=diag(1,𝐶2𝐶,,𝑁)is an 𝑀𝑁×𝑀𝑁product operational matrix. And, 𝐶𝑖,𝑖=1,2,3,,𝑁are 𝑀×𝑀matrices given by𝐶𝑖=𝑐𝑖0𝑐𝑖1𝑐𝑖2𝑐𝑖𝑀10𝑐𝑖0𝑐𝑖1𝑐𝑖𝑀200𝑐𝑖0𝑐𝑖𝑀3000𝑐𝑖0.(3.18)

4. Nonlinear Fredholm Integral Equations

Considering (1.1), we approximate 𝐷𝛼𝑓(𝑥) by the way mentioned in Section 3 as𝐷𝛼𝑓(𝑥)𝐴𝑇𝐻(𝑥).(4.1) For simplicity, we can assume that 𝛿𝑖=0(in the initial condition). Hence by using (2.5) and (3.13) we have𝑓(𝑥)𝐴𝑇𝑃𝛼𝐻(𝑥).(4.2) Define𝐴𝐶=𝑇𝑃𝛼𝑇,[]𝑓(𝑡)𝑞=𝐻𝑇(𝑡)𝐶𝑞=𝐶𝑇𝐻(𝑡)𝑚=𝐶𝑇𝐻(𝑡)𝐻𝑇𝐻(𝑡)𝐶𝑇(𝑡)𝐶𝑞2.(4.3) Applying (3.17) and (4.3) becomes[]𝑓(𝑡)𝑞=𝐴𝑇𝐻𝐶𝐻(𝑡)𝑇(𝑡)𝐶𝑞2=𝐶𝑇𝐶𝐻(𝑡)𝐻𝑇𝐻(𝑡)𝐶𝑇(𝑡)𝐶𝑞3,[]𝑓(𝑡)𝑞=𝐶𝑇𝐶𝑞1𝐻(𝑡)=𝐶𝐻(𝑡).(4.4) With substituting in (1.1) we have𝐴𝑇𝐻(𝑥)𝜆10𝑘(𝑥,𝑡)𝐶𝐻(𝑡)𝑑𝑡=𝑔(𝑥).(4.5) We now collocate (4.5) at 𝑁𝑀points𝑥𝑛𝑚=12𝑁cos𝑚𝜋+𝑀12𝑛12𝑁,𝑚=0,1,2,,𝑀1,𝑛=1,2,,𝑁,(4.6) as𝐴𝑇𝐻𝑥𝑛𝑚𝜆10𝑘𝑥𝑛𝑚𝐶,𝑡𝑥𝐻(𝑡)𝑑𝑡=𝑔𝑛𝑚.(4.7) We approximate above integral in (4.7) by means of Clenshaw-Curtis rule. Using (4.7), we obtain a system of 𝑁𝑀nonlinear equations which can be solved by the Newton’s iterative method. By solving this equation we can find the vector𝐶.

5. Error Analysis

In this section, we discuss the convergence of the hybrid functions method for the nonlinear Fredholm integro-differential equations (1.1).

Suppose we estimate function 𝑓(𝑥)𝐿2[0,1], using Taylor polynomials of order 𝑀1, on the interval [𝑎,𝑏], then using Taylor Residual Theorem, the truncation error is𝑒(𝑥)=𝑓(𝑥)𝑀1𝑖=0(𝑥𝑎)𝑖𝑓𝑖!(𝑖)(𝑎)=(𝑥𝑎)𝑀𝑓𝑀!(𝑀)(𝜉),(5.1) see, [24], where 𝜉lies between 𝑎 and 𝑥. Then𝑒(𝑥)(𝑏𝑎)𝑀𝑓𝑀!(𝑀)(𝑥).(5.2) If we use hybrid of block-pulse functions and Taylor series on the interval [0,1], then for 𝑖th sub interval [(𝑖1)/𝑁,𝑖/𝑁], we have𝑒(𝑥)=𝑓(𝑥)𝑓𝑁𝑀1(𝑥)𝑁𝑀𝑓𝑀!(𝑀)(𝑥)(5.3) see, [25], where the infinity norm is computed on the 𝑖th subinterval. It shows that the accuracy improves with increasing the𝑁 and 𝑀.

6. Numerical Examples

In this section, we applied the method presented in this paper for solving integral equation of the form (1.1) and solved some examples. All results were computed using MATLAB 7.0.

Example 6.1. Let us first consider fractional nonlinear intego-differential equation: 𝐷𝛼𝑓(𝑥)10[]𝑥𝑡𝑓(𝑡)2𝑥𝑑𝑡=14,0𝑥<1,0<𝛼1,(6.1) see, [26] with the initial condition 𝑓(0)=0.
The numerical results for 𝑀=1,𝑁=2,and 𝛼=1/4,1/2,3/4, and 1are plotted in Figure 1. For 𝛼=1, the exact solution is given as 𝑓(𝑥)=𝑥. Note that, as 𝛼approaches 1, the numerical solution converges the analytical solution 𝑓(𝑥)=𝑥.

Example 6.2. Consider the following equation: 𝐷1/2𝑓(𝑥)10[]𝑥𝑡𝑓(𝑡)2𝑑𝑡=𝑔(𝑥),(6.2) where 1𝑔(𝑥)=Γ(1/2)2𝑥1/283𝑥3/211𝑥11920,0𝑥2,8𝑥3Γ(1/2)3/221𝑥,11282<𝑥1,(6.3) and with these supplementary conditions 𝑓(0)=0. The exact solution is 𝑓(𝑥)=𝑥𝑥21,0𝑥2,𝑥2,12<𝑥1.(6.4) The absolute error |𝑓(𝑥)𝑓𝑁𝑀(𝑥)|for different values of 𝑁 and 𝑀 is shown in Table 1.

Example 6.3. One has 𝐷5/3𝑓(𝑥)10(𝑥+𝑡)2[]𝑓(𝑡)3𝑑𝑡=𝑔(𝑥),0𝑥<1,(6.5) see, [26] where 6𝑔(𝑥)=Γ(1/3)3𝑥𝑥27𝑥419,(6.6) and with these supplementary conditions 𝑓(0)=𝑓(0)=0. The exact solution is𝑓(𝑥)=𝑥2. Table 2 shows the exact and approximate solution for𝑁=2,𝑀=3. Figure 2 illustrates the absolute error |𝑓(𝑥)𝑓𝑁𝑀(𝑥)| with𝑁=10,𝑀=3. From Figure 2 and Table 2 we can see the numerical solutions are in a good agreement with the exact solution.

7. Conclusion

We have solved the nonlinear Fredholm integral equations of second kind by using hybrid of block-pulse functions and Taylor series. The properties of hybrid of block-pulse functions and Taylor series are used to reduce the equation to the solution of nonlinear algebraic equations. Illustrative examples are given to demonstrate the validity and applicability of the proposed method. The advantages of hybrid functions are that the values of 𝑁and 𝑀are adjustable as well as being able to yield more accurate numerical solutions. Also hybrid functions have good advantage in dealing with piecewise continuous functions, as are shown.

The method can be extended and applied to the system of nonlinear integral equations, linear and nonlinear integro-differential equations, but some modifications are required.

Acknowledgment

C. Yang is grateful to the National Natural Science Foundation of China (no. 40806011) for its support.