Steplength thresholds for invariance preserving of discretization methods of dynamical systems on a polyhedron

Zoltán Horváth; Yunfei Song; Tamás Terlaky

doi:10.3934/dcds.2015.35.2997

Article Contents

2015, Volume 35, Issue 7: 2997-3013. Doi: 10.3934/dcds.2015.35.2997

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Steplength thresholds for invariance preserving of discretization methods of dynamical systems on a polyhedron

1.
Department of Mathematics and Computational Sciences, Széchenyi István University, 9026 Győr, Egyetem tér 1
2.
Department of Industrial and Systems Engineering, Lehigh University, 200 West Packer Avenue, Bethlehem, PA, 18015-1582

Received: May 31, 2014

Revised: September 30, 2014

Published: May 2017

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Abstract

Steplength thresholds for invariance preserving of three types of discretization methods on a polyhedron are considered. For Taylor approximation type discretization methods we prove that a valid steplength threshold can be obtained by finding the first positive zeros of a finite number of polynomial functions. Further, a simple and efficient algorithm is proposed to numerically compute the steplength threshold. For rational function type discretization methods we derive a valid steplength threshold for invariance preserving, which can be computed by using an analogous algorithm as in the first case. The relationship between the previous two types of discretization methods and the forward Euler method is studied. Finally, we show that, for the forward Euler method, the largest steplength threshold for invariance preserving can be computed by solving a finite number of linear optimization problems.

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Mathematics Subject Classification: Primary: 34A30, 37M25, 65K05.

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References

[1]	D. Bertsimas and J. Tsitsiklis, Introduction to Linear Optimization, Athena Scientific, Nashua, 1998.
[2]	G. Bitsoris, On the positive invariance of polyhedral sets for discrete-time systems, System and Control Letters, 11 (1998), 243-248.doi: 10.1016/0167-6911(88)90065-5.
[3]	F. Blanchini, Set invariance in control, Automatica, 35 (1999), 1747-1767.doi: 10.1016/S0005-1098(99)00113-2.
[4]	F. Blanchini and S. Miani, Constrained stabilization of continuous-time linear systems, Systems and Control Letters, 28 (1996), 95-102.doi: 10.1016/0167-6911(96)00013-8.
[5]	F. Blanchini, S. Miani, C. E. T. Dórea and J. C. Hennet, Discussion on: '(A, B)- invariance conditions of polyhedral domains for continuous-time systems by C. E. T. Dórea and J.-C. Hennet', European Journal of Control, 5 (1999), 82-86.doi: 10.1016/S0947-3580(99)70142-1.
[6]	S. Boyd, L. El Ghaoui, E. Feron and V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory, SIAM Studies in Applied Mathematics, Philadelphia, 1994.doi: 10.1137/1.9781611970777.
[7]	E. B. Castelan and J. C. Hennet, On invariant polyhedra of continuous-time linear systems, IEEE Transactions on Automatic Control, 38 (1993), 1680-1685.doi: 10.1109/9.262058.
[8]	C. E. T. Dórea and J. C. Hennet, (A, B)-invariance conditions of polyhedral domains for continuous-time systems, European Journal of Control, 5 (1999), 70-81.
[9]	C. E. T. Dórea and J. C. Hennet, (A,B)-invariant polyhedral sets of linear discrete time systems, Journal of Optimization Theory and Applications, 103 (1999), 521-542.doi: 10.1023/A:1021727806358.
[10]	E. Hairer, S. P. Nørsett and G. Wanner, Solving Ordinary Differential Equations I: Nonstiff Problems, Springer-Verlag, New York, 1993.
[11]	N. J. Higham, Functions of Matrices: Theory and Computation, Society for Industrial and Applied Mathematics, Philadelphia, 2008.doi: 10.1137/1.9780898717778.
[12]	R. Horn and C. Johnson, Matrix Analysis, Cambridge University Press, Cambridge, 1990.
[13]	Z. Horváth, Invariant cones and polyhedra for dynamical systems, in Proceeding of the International Conference in Memoriam Gyula Farkas, Cluj Univ. Press, Cluj-Napoca, 2006, 65-74.
[14]	Z. Horváth, On the positivity step size threshold of Runge-Kutta methods, Applied Numerical Mathematics, 53 (2005), 341-356.doi: 10.1016/j.apnum.2004.08.026.
[15]	Z. Horváth, Y. Song and T. Terlaky, Invariance Preserving Discretization Methods of Dynamical Systems, Lehigh University, Department of Industrial and Systems Engineering, Technical Report 14T-009, 2014.
[16]	Z. Horváth, Y. Song and T. Terlaky, A Novel Unified Approach to Invariance in Control, Lehigh University, Department of Industrial and Systems Engineering, Technical Report 14T-003, 2014.
[17]	J. F. B. M. Kraaijevanger, Absolute monotonicity of polynomials occurring in the numerical solution of initial value problems, Numerische Mathematik, 48 (1986), 303-322.doi: 10.1007/BF01389477.
[18]	R. Loewy and H. Schneider, Positive operators on the $n$-dimensional ice cream cone, Journal of Mathematical Analysis and Applications, 49 (1975), 375-392.doi: 10.1016/0022-247X(75)90186-9.
[19]	C. Roos, T. Terlaky and J.-Ph. Vial, Interior Point Methods for Linear Optimization, Springer Science, Heidelberg, 2006.
[20]	M. N. Spijker, Contractivity in the numerical solution of initial value problems, Numerische Mathematik, 42 (1983), 271-290.doi: 10.1007/BF01389573.
[21]	R. Stern and H. Wolkowicz, Exponential nonnegativity on the ice cream cone, SIAM Journal on Matrix Analysis and Applications, 12 (1991), 160-165.doi: 10.1137/0612012.
[22]	B. Sturmfels, Solving Systems of Polynomial Equations, CBMS Lectures Series, American Mathematical Society, 2002.
[23]	J. Vandergraft, Spectral properties of matrices which have invariant cones, SIAM Journal on Applied Mathematics, 16 (1968), 1208-1222.doi: 10.1137/0116101.