State estimation and detectability of probabilistic discrete event systems

  • Authors:

  • Shaolong Shu;Feng Lin;Hao Ying;Xinguang Chen

  • Affiliations:

  • School of Electronics and Information Engineering, Tongji University, Shanghai, China;School of Electronics and Information Engineering, Tongji University, Shanghai, China and Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USA;Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USA;Pediatric Prevention Research Center, Wayne State University, Detroit, MI 48202, USA

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2008

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Abstract

A probabilistic discrete event system (PDES) is a nondeterministic discrete event system where the probabilities of nondeterministic transitions are specified. State estimation problems of PDES are more difficult than those of non-probabilistic discrete event systems. In our previous papers, we investigated state estimation problems for non-probabilistic discrete event systems. We defined four types of detectabilities and derived necessary and sufficient conditions for checking these detectabilities. In this paper, we extend our study to state estimation problems for PDES by considering the probabilities. The first step in our approach is to convert a given PDES into a nondeterministic discrete event system and find sufficient conditions for checking probabilistic detectabilities. Next, to find necessary and sufficient conditions for checking probabilistic detectabilities, we investigate the ''convergence'' of event sequences in PDES. An event sequence is convergent if along this sequence, it is more and more certain that the system is in a particular state. We derive conditions for convergence and hence for detectabilities. We focus on systems with complete event observation and no state observation. For better presentation, the theoretical development is illustrated by a simplified example of nephritis diagnosis.