期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 24, 期 12, 页码 2027-2037出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2013.2271357
关键词
Complex networks; coupling matrix; H-infinity state estimation; incomplete measurements; missing measurements; quantization; sensor saturations
类别
资金
- Engineering and Physical Sciences Research Council of the U.K. [GR/S27658/01]
- Royal Society of the U.K.
- National Natural Science Foundation of China [61134009, 61104125, 61203139]
- Shanghai Rising-Star Program of China [13QA1400100]
- Fundamental Research Funds for the Central Universities of China
- Alexander von Humboldt Foundation of Germany
In this paper, the H-infinity state estimation problem is investigated for a class of complex networks with uncertain coupling strength and incomplete measurements. With the aid of the interval matrix approach, we make the first attempt to characterize the uncertainties entering into the inner coupling matrix. The incomplete measurements under consideration include sensor saturations, quantization, and missing measurements, all of which are assumed to occur randomly. By introducing a stochastic Kronecker delta function, these incomplete measurements are described in a unified way and a novel measurement model is proposed to account for these phenomena occurring with individual probability. With the measurement model, a set of H-infinity state estimators is designed such that, for all admissible incomplete measurements as well as the uncertain coupling strength, the estimation error dynamics is exponentially mean-square stable and the H-infinity performance requirement is satisfied. The characterization of the desired estimator gains is derived in terms of the solution to a convex optimization problem that can be easily solved using the semidefinite program method. Finally, a numerical simulation example is provided to demonstrate the effectiveness and applicability of the proposed design approach.
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