Abstract

We provide a numerical method to solve a certain class of fractional differential equations involving $$\psi $$ -Caputo fractional derivative. The considered class includes as particular case fractional relaxation–oscillation equations. Our approach is based on operational matrix of fractional integration of a new type of orthogonal polynomials. More precisely, we introduce $$\psi $$ -shifted Legendre polynomial basis, and we derive an explicit formula for the $$\psi $$ -fractional integral of $$\psi $$ -shifted Legendre polynomials. Next, via an orthogonal projection on this polynomial basis, the problem is reduced to an algebraic equation that can be easily solved. The convergence of the method is justified rigorously and confirmed by some numerical experiments.

Highlights

  • A relaxation oscillator is an oscillator based upon the performance of a physical system’s resending to equilibrium after being disturbed

  • In [25], a generalized wavelet collocation operational matrix method based on Haar wavelets is proposed to solve (3) in which the fractional derivative is given in the Caputo sense

  • Our approach is based on operational matrix of fractional integration of a new type of orthogonal polynomials

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Summary

Introduction

A relaxation oscillator is an oscillator based upon the performance of a physical system’s resending to equilibrium after being disturbed. In [11], the authors used a Taylor matrix method in order to obtain the numerical solution of (3) by considering Caputo fractional derivative. This method is based on a fractional version of Taylor’s formula established in [21]. In [12], the numerical solution of (3) in which the fractional derivative is given in the Caputo sense, is obtained by the optimal homotopy asymptotic method. In [25], a generalized wavelet collocation operational matrix method based on Haar wavelets is proposed to solve (3) in which the fractional derivative is given in the Caputo sense.

Preliminaries
Operational matrices of integrations
Numerical scheme and convergence
Numerical results
Conclusion
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