Polynomial matrix analysis using symbolic computation

Author

Ogun, Ayowale B.

Author_Institution

GEG-PSE Process Controls, Air Products & Chem. Inc., Allentown, PA, USA

Volume

5

fYear

1998

fDate

21-26 Jun 1998

Firstpage

2657

Abstract

The polynomial matrix approach of Soderstrom et al. (1996), for the computation of the covariance function of a multivariate ARMA process, is implemented in a symbolic computing system (MapleV). Procedures were developed to solve the discrete-time symmetric matrix Diophantine equation and to compute the covariance function of a multivariate ARMA process. This algebraic implementation would have been extremely difficult to carry out in a strict numeric computing environment. The use of MapleV has provided symbolic results quickly and efficiently, with a tremendous gain in time and with minimal effort

Keywords

autoregressive moving average processes; covariance analysis; mathematics computing; polynomial matrices; symbol manipulation; MapleV; covariance function; multivariate ARMA process; polynomial matrix analysis; symbolic computation; symmetric Diophantine equation; Chemical processes; Chemical products; Control theory; Covariance matrix; Integral equations; Polynomials; Process control; Signal processing; Signal processing algorithms; Symmetric matrices;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1998. Proceedings of the 1998

Conference_Location

Philadelphia, PA

ISSN

0743-1619

Print_ISBN

0-7803-4530-4

Type

conf

DOI

10.1109/ACC.1998.688331

Filename

688331