Метод коллокации Чебышева для решения ОДУ второго порядка с использованием матриц интегрирования

Chebyshev collocation method for solving second order ODEs using integration matrices

The spectral collocation method for solving two-point boundary value problems for second order differential equations is implemented, based on representing the solution as an expansion in Chebyshev polynomials. The approach allows a stable calculation of both the spectral representation of the solution and its pointwise representation on any required grid in the definition domain of the equation and additional conditions of the multipoint problem. For the effective construction of SLAE, the solution of which gives the desired coefficients, the Chebyshev matrices of spectral integration are actively used. The proposed algorithms have a high accuracy for moderate-dimension systems of linear algebraic equations. The matrix of the system remains well-conditioned and, with an increase in the number of collocation points, allows finding solutions with ever-increasing accuracy.

Publisher
Федеральное государственное автономное образовательное учреждение высшего образования Российский университет дружбы народов (РУДН)
Number of issue
2
Language
English
Pages
150-163
Status
Published
Volume
31
Year
2023
Organizations
  • 1 Peoples’ Friendship University of Russia
  • 2 Joint Institute for Nuclear Research
Keywords
ordinary differential equation; spectral methods; two-point boundary value problems; обыкновенное дифференциальное уравнение; спектральные методы; двухточечные краевые задачи
Date of creation
07.07.2023
Date of change
10.07.2023
Short link
https://repository.rudn.ru/en/records/article/record/93616/
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Gevorkyan Migran N., Korolkova Anna V., Kulyabov Dmitry S.
Discrete and Continuous Models and Applied Computational Science. Федеральное государственное автономное образовательное учреждение высшего образования Российский университет дружбы народов (РУДН). Vol. 31. 2023. P. 139-149
Malykh Mikhail D., Chusovitina Polina S.
Discrete and Continuous Models and Applied Computational Science. Федеральное государственное автономное образовательное учреждение высшего образования Российский университет дружбы народов (РУДН). Vol. 31. 2023. P. 164-173