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DC Field | Value | Language |
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dc.contributor.author | Wang, Z | - |
dc.contributor.author | Shen, B | - |
dc.contributor.author | Liu, X | - |
dc.date.accessioned | 2012-03-19T11:28:30Z | - |
dc.date.available | 2012-03-19T11:28:30Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Automatica, 48(3): 556 - 562, Mar 2012 | en_US |
dc.identifier.issn | 0005-1098 | - |
dc.identifier.uri | http://www.sciencedirect.com/science/article/pii/S0005109812000222 | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/6315 | - |
dc.description | This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 Elsevier | en_US |
dc.description.abstract | In this paper, the H∞ filtering problem is investigated for a class of nonlinear systems with randomly occurring incomplete information. The considered incomplete information includes both the sensor saturations and the missing measurements. A new phenomenon of sensor saturation, namely, randomly occurring sensor saturation (ROSS), is put forward in order to better reflect the reality in a networked environment such as sensor networks. A novel sensor model is then established to account for both the ROSS and missing measurement in a unified representation by using two sets of Bernoulli distributed white sequences with known conditional probabilities. Based on this sensor model, a regional H∞ filter with a certain ellipsoid constraint is designed such that the filtering error dynamics is locally mean-square asymptotically stable and the H∞-norm requirement is satisfied. Note that the regional l2 gain filtering feature is specifically developed for the random saturation nonlinearity. The characterization of the desired filter gains is derived in terms of the solution to a convex optimization problem that can be easily solved by using the semi-definite program method. Finally, a simulation example is employed to show the effectiveness of the filtering scheme proposed in this paper. | en_US |
dc.description.sponsorship | This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61028008 and 60974030, the National 973 Program of China under Grant 2009CB320600, and the Alexander von Humboldt Foundation of Germany. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | Randomly occurring sensor saturations | en_US |
dc.subject | Missing measurements | en_US |
dc.subject | Nonlinear systems | en_US |
dc.subject | Regional H∞ filters | en_US |
dc.subject | Random incomplete information | en_US |
dc.title | H-infinity filtering with randomly occurring sensor saturations and missing measurements | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/j.automatica.2012.01.008 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel Active Staff | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths/IS and Computing | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Centre for Systems and Synthetic Biology | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Centre for Information and Knowledge Management | - |
Appears in Collections: | Publications Computer Science Dept of Computer Science Research Papers |
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