Integrating Lipschitzian dynamical systems using piecewise algorithmic differentiation

In this article we analyse a generalized trapezoidal rule for initial value problems with piecewise smooth right-hand side based on a generalization of algorithmic differentiation. When applied to such a problem, the classical trapezoidal rule suffers from a loss of accuracy if the solution trajectory intersects a nondifferentiability of F. The advantage of the proposed generalized trapezoidal rule is threefold: Firstly, we can achieve a higher convergence order than with the classical method. Moreover, the method is energy preserving for piecewise linear Hamiltonian systems. Finally, in analogy to the classical case we derive a third-order interpolation polynomial for the numerical trajectory. In the smooth case, the generalized rule reduces to the classical one. Hence, it is a proper extension of the classical theory. An error estimator is given and numerical results are presented.

[1]  Uwe Naumann,et al.  The Art of Differentiating Computer Programs - An Introduction to Algorithmic Differentiation , 2012, Software, environments, tools.

[2]  Mario di Bernardo,et al.  Piecewise smooth dynamical systems , 2008, Scholarpedia.

[3]  G. Quispel,et al.  A new class of energy-preserving numerical integration methods , 2008 .

[4]  Arnold Neumaier,et al.  Introduction to Numerical Analysis , 2001 .

[5]  Philippe Chartier,et al.  GEOMETRIC INTEGRATORS FOR PIECEWISE SMOOTH HAMILTONIAN SYSTEMS , 2008 .

[6]  P. Hartman Ordinary Differential Equations , 1965 .

[7]  Andreas Griewank,et al.  Evaluating derivatives - principles and techniques of algorithmic differentiation, Second Edition , 2000, Frontiers in applied mathematics.

[8]  L. Shampine,et al.  Event location for ordinary differential equations , 2000 .

[9]  Manuel Radons,et al.  Direct solution of piecewise linear systems , 2016, Theor. Comput. Sci..

[10]  Begnaud Francis Hildebrand,et al.  Introduction to numerical analysis: 2nd edition , 1987 .

[11]  Andreas Griewank,et al.  Representation and Analysis of Piecewise Linear Functions in Abs-Normal Form , 2013, System Modelling and Optimization.

[12]  Andreas Griewank,et al.  Piecewise linear secant approximation via algorithmic piecewise differentiation , 2017, Optim. Methods Softw..

[13]  W. H. Enright,et al.  Effective solution of discontinuous IVPs using a Runge-Kutta formula pair with interpolants , 1988 .

[14]  S. Scholtes Introduction to Piecewise Differentiable Equations , 2012 .

[15]  Andreas Griewank,et al.  On stable piecewise linearization and generalized algorithmic differentiation , 2013, Optim. Methods Softw..

[16]  A. Griewank,et al.  Solving piecewise linear systems in abs-normal form , 2015, 1701.00753.

[17]  F. Clarke Optimization And Nonsmooth Analysis , 1983 .

[18]  F. Krogh,et al.  Solving Ordinary Differential Equations , 2019, Programming for Computations - Python.