Computational Complexity of

The structured singular value μ measures the robustness of uncertain Systems. Numerous researchers over the last decade have worked on developing efficient methods for computing μ. This paper considers the complexity of calculating μ with general mixed real/complex uncertainty in the framework of combinatorial complexity theory. In particular, it is proved that the μ recognition problem with either pure real or mixed real/complex uncertainty is NP-hard. This strongly suggests that it is futile to pursue exact methods for calculating μ of general systems with pure real or mixed uncertainty for other than small problems.

[1]  Kenneth Steiglitz,et al.  Combinatorial Optimization: Algorithms and Complexity , 1981 .

[2]  John C. Doyle Analysis of Feedback Systems with Structured Uncertainty , 1982 .

[3]  Katta G. Murty,et al.  Some NP-complete problems in quadratic and nonlinear programming , 1987, Math. Program..

[4]  Stephen A. Vavasis,et al.  Quadratic Programming is in NP , 1990, Inf. Process. Lett..

[5]  Rama K. Yedavalli,et al.  Recent Advances in Robust Control , 1990 .

[6]  J. Doyle,et al.  mu analysis with real parametric uncertainty , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.

[7]  C. Nett,et al.  On μ and stability of uncertain polynomials , 1992, 1992 American Control Conference.

[8]  James Demmel,et al.  The Componentwise Distance to the Nearest Singular Matrix , 1992, SIAM J. Matrix Anal. Appl..

[9]  Svatopluk Poljak,et al.  Checking robust nonsingularity is NP-hard , 1993, Math. Control. Signals Syst..

[10]  A. Packard,et al.  Continuity properties of the real/complex structured singular value , 1993, IEEE Trans. Autom. Control..