15th Triennial World Congress of the International Federation of Automatic Control
  Barcelona, 21–26 July 2002 
POLYNOMIAL BASES FOR OPTIMAL WORST CASE APPROXIMATION OF NONLINEARITIES
Gustavo Belforte* Paolo Gay**
* Dipartimento di Automatica e Informatica
Politecnico di Torino
corso Duca degli Abruzzi 24, Torino - Italy
** Dipartimento di Economia e Ingegneria Agraria
Forestale e Ambientale
Università degli Studi di Torino
via Leonardo da Vinci 44, Grugliasco (TO) - Italy

Several identification and control problems present nonlinearities that cannot be neglected and are often approximated by polynomials. In some previous works optimal set of interpolation nodes that minimizes the uncertainties of the approximation have been derived for the Vandermonde base that, however, can lead to ill-conditioned numerical problems.
In this paper the conditions under which polynomial bases, used for representing static nonlinear blocks, derived by linear transformation from the Vandermonde base preserve the optimal worst case design features of the Vandermonde base are investigated.
Explicit meaningful geometrical and analytical conditions to which the transformation matrix must satisfy in order to allow the new base to mantain the optimal sampling schedule of the Vandermonde matrix are derived.
Keywords: Optimal experiment design, Optimal sampling, Set-membership identification, Polynomials
Session slot T-Th-E01: Identification of Nonlinear Systems III/Area code 3a : Modelling, Identification and Signal Processing