DocumentCode
811274
Title
On Positivity of Polynomials: The Dilation Integral Method
Author
Barmish, B. Ross ; Shcherbakov, Pavel S. ; Ross, Sheila R. ; Dabbene, Fabrizio
Volume
54
Issue
5
fYear
2009
fDate
5/1/2009 12:00:00 AM
Firstpage
965
Lastpage
978
Abstract
The focal point of this paper is the well known problem of polynomial positivity over a given domain. More specifically, we consider a multivariate polynomial f(x) with parameter vector x restricted to a hypercube X sub R n. The objective is to determine if f(x) > 0 for all x isin X. Motivated by NP-Hardness considerations, we introduce the so-called dilation integral method. Using this method, a ldquosofteningrdquo of this problem is described. That is, rather than insisting that f(x) be positive for all x isin X, we consider the notions of practical positivity and practical non-positivity. As explained in the paper, these notions involve the calculation of a quantity epsiv > 0 which serves as an upper bound on the percentage volume of violation in parameter space where f(x) les 0 . Whereas checking the polynomial positivity requirement may be computationally prohibitive, using our epsiv-softening and associated dilation integrals, computations are typically straightforward. One highlight of this paper is that we obtain a sequence of upper bounds epsivk which are shown to be ldquosharprdquo in the sense that they converge to zero whenever the positivity requirement is satisfied. Since for fixed n , computational difficulties generally increase with k, this paper also focuses on results which reduce the size of the required k in order to achieve an acceptable percentage volume certification level. For large classes of problems, as the dimension of parameter space n grows, the required k value for acceptable percentage volume violation may be quite low. In fact, it is often the case that low volumes of violation can be achieved with values as low as k=2.
Keywords
computational complexity; polynomials; NP-hardness; dilation integral method; multivariate polynomial; polynomial positivity; positivity requirement; Certification; Controllability; Hypercubes; Numerical analysis; Polynomials; Risk analysis; Robust control; Robustness; Uncertain systems; Upper bound; Approximation methods; integration; numerical analysis; polynomials; risk analysis; robustness; uncertain systems;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.2009.2017115
Filename
4908938
Link To Document