Methods of stochastic diagnostic type observers

Andrzej Kotyra, Andrii Volovyk, Lyudmila Krylik, Iryna M. Kobylyanska, Saltanat N. Amirgaliyeva

2018

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DOI 10.1117/12.2501693
Data confidence 70 medium
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Abstract

The paper considers the fundamentals of the design theory of stochastic diagnostic type observers that are invariant to unknown inputs. It presents a description of identification and malfunctions localization problem when the noise is present. The article provides theoretical substantiation of the decomposition procedure of optimal stochastic observers with indefinite inputs and noise. Optimality criterions of such observer are defined. The paper reveals invariance of a differential signal in relation to indefinite, uncontrollable perturbations. Optionally, in a case, when a differential signal has a Gaussian distribution, the procedure of decision making about fault availability is offered.