Journal
IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 17, Issue 2, Pages 398-410Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2009.2014860
Keywords
Basis-dependent Lyapunov functions; fault detection; intermittent measurements; Takagi-Sugeno (T-S) fuzzy systems; uncertainties
Funding
- National Natural Science Foundation of China [60825303, 60834003]
- 973 Project [2009CB320600]
- Research Fund for the Doctoral Programme of Higher Education of China [20070213084]
- Heilongjiang Outstanding Youth Science Fund [JC200809]
- Postdoctoral Science Foundation of China [200801282]
- University of Hong Kong Research
- Conference Grants (CRCG) [200707176077]
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This paper investigates the problem of fault detection for Takagi-Sugeno (T-S) fuzzy systems with intermittent measurements. The communication links between the plant and the fault detection filter are assumed to be imperfect (i.e., data packet dropouts occur intermittently, which appear typically in a network environment), and a stochastic variable satisfying the Bernoulli random binary distribution is utilized to model the unreliable communication links. The aim is to design a fuzzy fault detection filter such that, for all data missing conditions, the residual system is stochastically stable and preserves a guaranteed performance. The problem is solved through a basis-dependent Lyapunov function method, which is less conservative than the quadratic approach. The results are also extended to T-S fuzzy systems with time-varying parameter uncertainties. All the results are formulated in the form of linear matrix inequalities, which can be readily solved via standard numerical software. Two examples are provided to illustrate the usefulness and applicability of the developed theoretical results.
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