Journal
NEUROCOMPUTING
Volume 214, Issue -, Pages 340-349Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2016.06.016
Keywords
Networked systems; Time-varying systems; Fault estimation; Packet dropouts; Randomly occurring uncertainties; Performance analysis
Categories
Funding
- National Natural Science Foundation of China [11301118, 11271103]
- Fok Ying Tung Education Foundation of China [151004]
- Science Funds for the Young Innovative Talents of HUST
- Youth Science Foundation of Heilongjiang Province of China [QC2015085]
- University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province
- China Postdoctoral Science Foundation [2015T80482, 2014M560376]
- Jiangsu Planned Projects for Postdoctoral Research Funds [1402004A]
- Alexander von Humboldt Foundation of Germany
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In this paper, we discuss the fault estimation problem for a class of time-varying networked systems in the simultaneous presence of randomly occurring uncertainties, stochastic nonlinearities and packet dropouts. The phenomena of the randomly occurring uncertainties and packet dropouts are characterized by utilizing mutually independent random variables with known occurrence probabilities. The stochastic nonlinearities are also considered which can cover many known nonlinearities as special cases. The major focus is on the design of the fault estimation algorithm such that, for all randomly occurring uncertainties, stochastic nonlinearities and packet dropouts, an optimized upper bound of the estimation error covariance is derived at each time step and the explicit form of the estimator gain is provided. As a by-product, the unknown system state is estimated simultaneously. It should be noted that a new compensation scheme is introduced to improve the estimation performance by properly using the statistical property of the imperfect measurements. In addition, the monotonicity of the trace of such an optimal upper bound with respect to the missing probability is revealed from theoretical perspective. Finally, the usefulness of the proposed estimation compensation scheme is demonstrated by a simulation example. (C) 2016 Elsevier B.V. All rights reserved.
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