Short communication: New results in modelling derived from Bayesian filtering

Authors:
Claudiu Pozna;Radu-Emil Precup;József K. Tar;Igor Škrjanc;Stefan Preitl
Affiliations:
Department of Product Design and Robotics, Transilvania University of Brasov, Bd. Eroilor 28, 500036 Brasov, Romania;Department of Automation and Applied Informatics, "Politehnica" University of Timisoara, Bd. V. Parvan 2, 300223 Timisoara, Romania;Institute of Intelligent Engineering Systems, Budapest Tech Polytechnical Institution, Bécsi út 96/B, H-1034 Budapest, Hungary;Faculty of Electrical Engineering, Laboratory of Modelling, Simulation and Control, University of Ljubljana, Traška 25, 1000 Ljubljana, Slovenia;Department of Automation and Applied Informatics, "Politehnica" University of Timisoara, Bd. V. Parvan 2, 300223 Timisoara, Romania
Venue:
Knowledge-Based Systems
Year:
2010

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Abstract

This paper suggests an original heuristic modelling algorithm expressed in terms of homogenous combinations of the classical system dynamics and the Bayesian degree of truth employed in modelling. The main benefits of the proposed approach compared to classical modelling are the increased transparency and alleviated computational time. Two case studies, dealing with a mobile robot and an unforced pendulum system, are included to exemplify and test the theoretical results. One of the case studies makes use of the definition and calculation of several discrete plausibilities.