Finding the distance to instability of a large sparse matrix

The distance to instability of a matrix A is a robust measure for the stability of the corresponding dynamical system x = Ax, known to be far more reliable than checking the eigenvalues of A. In this paper, a new algorithm for computing such a distance is sketched. Built on existing approaches, its computationally most expensive part involves a usually modest number of shift-and-invert Amoldi iterations. This makes it possible to address large sparse matrices, such as those arising from discretized partial differential equations.


Published in:
2006 IEEE Conference on Computer-Aided Control System Design, Vols 1 and 2, 31-35
Presented at:
IEEE Conference on Computer-Aided Control Systems Design, Munich, Germany, Oct 04-06, 2006
Year:
2006
Publisher:
IEEE
Keywords:
Laboratories:




 Record created 2011-05-05, last modified 2018-03-17

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