Abstract
In Chap. 6, we consider a new distributed H ∞−consensus filtering problem over a finite horizon for sensor networks with multiple missing measurements. The so-called H ∞−consensus performance requirement is defined to quantify bounded consensus regarding the filtering errors (agreements) over a finite horizon. A sufficient condition is first established in terms of a set of difference linear matrix inequalities (DLMIs) under which the expected H ∞-consensus performance constraint is guaranteed. Then, the filter parameters are explicitly parameterized by means of the solutions to a certain set of DLMIs that can be computed recursively. Subsequently, two kinds of robust distributed H ∞−consensus filters are designed for the systems with norm-bounded uncertainties and polytopic uncertainties.
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Shen, B., Wang, Z., Shu, H. (2013). Distributed H ∞-Consensus Filtering in Sensor Networks. In: Nonlinear Stochastic Systems with Incomplete Information. Springer, London. https://doi.org/10.1007/978-1-4471-4914-9_6
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DOI: https://doi.org/10.1007/978-1-4471-4914-9_6
Publisher Name: Springer, London
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