An optimal linear prediction filter for discrete-time linear additive hybrid systems

Ford, Jason J. (2016) An optimal linear prediction filter for discrete-time linear additive hybrid systems. In Australian Control Conference, 3-4 November 2016, Newcastle, NSW. (In Press)

Abstract

Discrete-time linear additive hybrid systems arise in many applications of interest including estimation for systems experiencing unobserved command or disturbance inputs. Optimal conditional mean estimation for these systems generally involves infinite dimensional non-linear filters. In this paper, we instead proposed an optimal minimum variance linear prediction filter. A simulation example is included which highlights the features of these predictors.

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ID Code: 99596
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Hidden Markov Model, Estimation, Hybrid Systems, Filter
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2016 [please consult the author]
Deposited On: 27 Sep 2016 22:43
Last Modified: 05 Nov 2016 06:32

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