access icon free Fault detection for a class of non-linear networked control systems in the presence of Markov sensors assignment with partially known transition probabilities

In this study, the problem of fault detection for a class of discrete-time non-linear networked control systems is investigated. An event modelled as a Markov chain taking matrix values in a certain set with partially known transition probabilities is utilised to characterise the phenomenon of the sensors assignment. A full-order mode-dependent fault detection filter is constructed and the corresponding fault detection problem is converted into an H filtering problem of a Markov jump system with partially known transition probabilities. Sufficient conditions for the existence of the fault detection filter are formulated as a linear matrix inequality-based convex optimisation problem. If the convex optimisation problem has a feasible solution, the corresponding fault detection filter parameters are determined. A numerical example with four cases of transition probability matrices is presented to show the usefulness of the developed method.

Inspec keywords: nonlinear control systems; networked control systems; convex programming; probability; linear matrix inequalities; H∞ filters; discrete time systems; multivariable control systems; Markov processes

Other keywords: H∞ filtering problem; linear matrix inequality; nonlinear networked control systems; fault detection filter; discrete time nonlinear networked control systems; Markov chain; transition probabilities; convex optimisation problem; matrix values; Markov sensors assignment; Markov jump system; sensors assignment

Subjects: Algebra; Nonlinear control systems; Multivariable control systems; Markov processes; Discrete control systems; Optimisation techniques

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http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2013.0802
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