Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities
© 2016 ISSN.A robust fault detection observer (RFDO) is designed to solve the robust fault detection problem of the nonlinear Markovian jump systems (NMJSs) with partly unknown transition probabilities. With the method of T-S fuzzy linearization, the original NMJSs are described as a set of local li...
| Main Authors: | , , |
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| Format: | Journal Article |
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ICIC International
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/63111 |
| Summary: | © 2016 ISSN.A robust fault detection observer (RFDO) is designed to solve the robust fault detection problem of the nonlinear Markovian jump systems (NMJSs) with partly unknown transition probabilities. With the method of T-S fuzzy linearization, the original NMJSs are described as a set of local linear models. On this basis, free-connection weighting matrices are introduced to RFDO. A series of linear matrix inequalities which ensure the stochastic asymptotic stability of the system are obtained by using the constructed Lyapunov function. Furthermore, the design problem is formulated as a two-objective optimization algorithm. A simulation example is given to show that the designed RFDO can not only detect the fault sensitively, but have the robustness to unknown disturbances. |
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