Practical stability of approximating discrete-time filters with respect to model mismatch

Authors:
Onvaree Techakesari;Jason J. Ford;Dragan NešIć
Affiliations:
School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane QLD 4001, Australia;School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane QLD 4001, Australia;Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville VIC 3010, Australia
Venue:
Automatica (Journal of IFAC)
Year:
2012

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Abstract

This paper establishes practical stability results for an important range of approximate discrete-time filtering problems involving mismatch between the true system and the approximating filter model. Practical stability is established in the sense of an asymptotic bound on the amount of bias introduced by the model approximation. Our analysis applies to a wide range of estimation problems and justifies the common practice of approximating intractable infinite dimensional nonlinear filters by simpler computationally tractable filters.