Author :
Barmish, B. Ross ; Shcherbakov, Pavel S. ; Ross, Sheila R. ; Dabbene, Fabrizio
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;