Finite-dimensional risk-sensitive filters and smoothers for discrete-time nonlinear systems

Author

Dey, Subhrakanti ; Moore, John B.

Author_Institution

Dept. of Syst. Eng., Australian Nat. Univ., Canberra, ACT, Australia

Volume

44

Issue

6

fYear

1999

fDate

6/1/1999 12:00:00 AM

Firstpage

1234

Lastpage

1239

Abstract

Finite-dimensional optimal risk-sensitive filters and smoothers are obtained for discrete-time nonlinear systems by adjusting the standard exponential of a quadratic risk-sensitive cost index to one involving the plant nonlinearity. It is seen that these filters and smoothers are the same as those for a fictitious linear plant with the exponential of squared estimation error as the corresponding risk-sensitive cost index. Such finite-dimensional filters do not exist for nonlinear systems in the case of minimum variance filtering and control

Keywords

discrete time filters; filtering theory; multidimensional systems; nonlinear systems; optimisation; Finite-dimensional optimal risk-sensitive smoothers; discrete-time nonlinear systems; finite-dimensional optimal risk-sensitive filters; linear plant; minimum variance control; minimum variance filtering; plant nonlinearity; quadratic risk-sensitive cost index; squared estimation error; standard exponential; Automatic control; Control systems; Filters; Nonlinear systems; Poles and zeros; Polynomials; Robust control; Sampling methods; Taylor series; Transfer functions;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.769381

Filename

769381