Information Theoretical Approach to Identification of Hybrid Systems

Authors:
Li Pu;Jinchun Hu;Badong Chen
Affiliations:
State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing, China 100084;State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing, China 100084;State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing, China 100084
Venue:
HSCC '08 Proceedings of the 11th international workshop on Hybrid Systems: Computation and Control
Year:
2008

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Abstract

In this paper, we present a noisy version of the algebraic geometric approach of identifying parameters of discrete-time linear hybrid system. Two approximate ways of estimating hybrid parameters are considered: one is using MSE criteria, while the other is based on the information divergence that measures the distance between the error probability density function (PDF) of the identified model and the desired error PDF. A stochastic information divergence gradient algorithm is derived for the identification problem of non-gaussian system.