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A particle filtering method is implemented within a log-likelihood ratio approach here specifically tailored to handle hybrid dynamic systems, i.e, systems characterized by transitions among discrete modes of operation and failure, each one giving rise to a specific continuous dynamics of evolution. An application to a case study of literature proves the capabilities of the newly devised algorithm.
System dynamics estimation is a crucial issue for the safe operation and control of nuclear power plants. Typically, the estimation is based on a model of the plant dynamics and related measurements. In practice, the non-linearity of the dynamics and non-Gaussianity of the noise associated to the process and measurements lead to inaccurate results even with advanced approaches, such as the Kalman,...
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