Entropy Optimization Filtering for Fault Isolation of Nonlinear Non-Gaussian Stochastic Systems
| Autor: | Lei Guo, Tianyou Chai, Hong Wang, Liping Yin |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Gaussian
System identification Probability density function Filter (signal processing) Nonlinear control Fault detection and isolation Computer Science Applications Nonlinear system symbols.namesake Control and Systems Engineering Control theory symbols Entropy (information theory) Electrical and Electronic Engineering Entropy optimization fault isolation non-Gaussian systems non-linear filtering optimal control Algorithm Mathematics |
| Zdroj: | IEEE Transactions on Automatic Control. 54:804-810 |
| ISSN: | 1558-2523 0018-9286 |
| DOI: | 10.1109/tac.2008.2009599 |
| Popis: | In this paper, the fault isolation (FI) problem is investigated for nonlinear non-Gaussian systems with multiple faults(or abrupt changes of system parameters) in the presence of noises. By constructing a filter to estimate the states, the FI problem can be reduced to an entropy optimization problem subjected to the non-Gaussian estimation error systems. The design objective for the FI purpose is that the entropy of the estimation error is maximized in the presence of diagnosed fault and is minimized in the presence of the nuisance faults or noises. It is shown that the error dynamics is represented by a nonlinear non-Gaussian stochastic system, for which new relationships are applied to formulate the probability density functions (PDFs) of the stochastic error in terms of the PDFs of the noises and the faults. The Renyi?s entropy has been used to simplify the computations in the filtering for the recursive design algorithms. It is noted that the output can be supposed to be immeasurable (but with known stochastic distributions), which is different from the existing results where the output is always measurable for feedback. Finally, simulations are given to demonstrate the effectiveness of the proposed data-driven FI filtering algorithms. |
| Databáze: | OpenAIRE |
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