Embedded symmetric nested implicit Runge–Kutta methods of Gauss and Lobatto types for solving stiff ordinary differential equations and Hamiltonian systems

被引:0
作者
G. Yu. Kulikov
机构
[1] Universidade de Lisboa,CEMAT, Instituto Superior Técnico
来源
Computational Mathematics and Mathematical Physics | 2015年 / 55卷
关键词
numerical methods; solutions of ordinary differential equations; nested implicit Runge–Kutta method; embedded formulas; Runge–Kutta methods of Gauss and Lobatto types; automatic error control; stiff initial value problem; Hamiltonian equations;
D O I
暂无
中图分类号
学科分类号
摘要
A technique for constructing nested implicit Runge–Kutta methods in the class of mono-implicit formulas of this type is studied. These formulas are highly efficient in practice, since the dimension of the original system of differential equations is preserved, which is not possible in the case of implicit multistage Runge–Kutta formulas of the general from. On the other hand, nested implicit Runge-Kutta methods inherit all major properties of general formulas of this form, such as A-stability, symmetry, and symplecticity in a certain sense. Moreover, they can have sufficiently high stage and classical orders and, without requiring high extra costs, can ensure dense output of integration results of the same accuracy as the order of the underlying method. Thus, nested methods are efficient when applied to the numerical integration of differential equations of various sorts, including stiff and nonstiff problems, Hamiltonian systems, and invertible equations. In this paper, previously proposed nested methods based on the Gauss quadrature formulas are generalized to Lobatto-type methods. Additionally, a unified technique for constructing all such methods is proposed. Its performance is demonstrated as applied to embedded examples of nested implicit formulas of various orders. All the methods constructed are supplied with tools for local error estimation and automatic variable-stepsize mesh generation based on an optimal stepsize selection. These numerical methods are verified by solving test problems with known solutions. Additionally, a comparative analysis of these methods with Matlab built-in solvers is presented.
引用
收藏
页码:983 / 1003
页数:20
相关论文
共 82 条
[1]  
Konyukhova N. B.(2008)Bubbles and droplets in nonlinear physics models: Analysis and numerical simulation of singular nonlinear boundary value problems Comput. Math. Math. Phys. 48 2018-2058
[2]  
Lima P. M.(2006)Analytical-numerical investigation of bubble-type solutions of nonlinear singular problems J. Comput. Appl. Math. 189 260-273
[3]  
Morgado M. L.(2014)Analysis and numerical approximation of singular boundary value problems with P-Laplacian in fluid mechanics J. Comput. Appl. Math. 262 87-104
[4]  
Soloviev M. B.(2012)Various ways to compute the continuous-discrete extended Kalman filter IEEE Trans. Autom. Control 57 1000-1004
[5]  
Lima P. M.(2014)Accurate numerical implementation of the continuous-discrete extended Kalman filter IEEE Trans. Autom. Control 59 273-279
[6]  
Konyukhova N. B.(2014)Adaptive ODE solvers in extended Kalman filtering algorithms J. Comput. Appl. Math. 262 205-216
[7]  
Chemetov N. V.(1976)On the implementation of implicit Runge–Kutta methods BIT 16 237-240
[8]  
Sukov A. I.(1977)An efficient solution process for implicit Runge–Kutta methods SIAM J. Numer. Anal. 14 1022-1027
[9]  
Kulikov G. Y.u.(1977)On the class of implicit Runge–Kutta procedures J. Inst. Math. Appl. 19 455-470
[10]  
Lima P. M.(1977)On a note of the computational aspects of the class of implicit Runge–Kutta procedures J. Inst. Math. Appl. 20 425-441