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Title: | Receding horizon filtering for a class of discrete time-varying nonlinear systems with multiple missing measurements |
Authors: | Ding, D Wang, Z Alsaadi, FE Shen, B |
Keywords: | Discrete time-varying systems;Multiple missing measurements;Receding horizon filtering;Stochastic nonlinear |
Issue Date: | 2015 |
Publisher: | Taylor and Francis Ltd. |
Citation: | International Journal of General Systems, 44(2): 198 - 211, (2015) |
Abstract: | This paper is concerned with the receding horizon filtering problem for a class of discrete time-varying nonlinear systems with multiple missing measurements. The phenomenon of missing measurements occurs in a random way and the missing probability is governed by a set of stochastic variables obeying the given Bernoulli distribution. By exploiting the projection theory combined with stochastic analysis techniques, a Kalman-type receding horizon filter is put forward to facilitate the online applications. Furthermore, by utilizing the conditional expectation, a novel estimation scheme of state covariance matrices is proposed to guarantee the implementation of the filtering algorithm. Finally, a simulation example is provided to illustrate the effectiveness of the established filtering scheme. |
URI: | http://www.tandfonline.com/doi/abs/10.1080/03081079.2014.973732# http://bura.brunel.ac.uk/handle/2438/10664 |
DOI: | http://dx.doi.org/10.1080/03081079.2014.973732 |
ISSN: | 0308-1079 1563-5104 |
Appears in Collections: | Dept of Computer Science Research Papers |
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