Particle filtering for the estimation of system mode of operation

• Autorzy: Cadini F. , Avram D. , Zio E.
• Języki publikacji: EN

Abstrakty

EN

Efficient diagnosis and prognosis of system faults depend on the ability to estimate the system state on the basis of noisy measurements of the system dynamic variables and parameters. The system dynamics is typically characterized by transitions among discrete modes of operation, each one giving rise to a specific continuous dynamics of evolution. The estimation of the state of these hybrid dynamic systems is a particularly challenging task because it requires keeping track of the transitions among the multiple modes of system dynamics corresponding to the different modes of operation. In this paper a Monte Carlo estimation method is illustrated with an application to a case study of literature which consists of a tank filled with liquid, whose level is autonomously maintained between two thresholds. The system behavior is controlled by discrete mode actuators, whose states are estimated by a Monte Carlo-based particle filter on the basis of noisy level and temperature measurements.

Słowa kluczowe

EN

particle filtering; Monte Carlo; hybrid system; discrete modes of operation

• Wydawca: Polskie Towarzystwo Bezpieczeństwa i Niezawodności
• Czasopismo: Journal of Polish Safety and Reliability Association
• Rocznik: 2009
• Tom: Vol. 1
• Strony: 77--86
• Opis fizyczny: Bibliogr. 23 poz., rys., tab., wykr.

Twórcy

autor

Cadini F.

• Politecnico di Milano – Dipartimento di Energia, Milan, Italy

autor

Avram D.

• Politecnico di Milano – Dipartimento di Energia, Milan, Italy

autor

Zio E.

• Politecnico di Milano – Dipartimento di Energia, Milan, Italy

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