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)


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.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

9 since deposited on 27 Sep 2016
9 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

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

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page