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A riccati equation approach to the singular LQG problem

dc.contributor.authorHalevi, Yoramen_US
dc.contributor.authorHaddad, Wassim M.en_US
dc.contributor.authorBernstein, Dennis S.en_US
dc.date.accessioned2006-04-10T15:46:45Z
dc.date.available2006-04-10T15:46:45Z
dc.date.issued1993-05en_US
dc.identifier.citationHalevi, Yoram, Haddad, Wassim M., Bernstein, Dennis S. (1993/05)."A riccati equation approach to the singular LQG problem." Automatica 29(3): 773-778. <http://hdl.handle.net/2027.42/30823>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V21-47WTGM1-XN/2/04cb322c8543582b062146b5326ca516en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/30823
dc.description.abstractThe problem of optimal fixed-order dynamic compensation for the singular LQG problem is considered. Necessary conditions characterizing the optimal compensator for the case involving both singular measurement noise and singular control weighting are given. The solution consists of a set of two algebraic Riccati equations and two Lyapunov equations coupled by three projection matrices. One projection is the standard order reduction projection while the other two projections reflect the two types of singularity that exist in the system. The three projections are shown to satisfy disjointness conditions. In addition to order reduction, an advantage of the fixed-structure approach is that differentiation, which is often undersirable from a practical point of view and which may exist in the unconstrained optimal control, can be avoided. It is shown that the fixed-order compensator agrees with the unconstrained solution when the latter possesses the same number of differentiations as are included in the prespecified controller structure and when the order is selected appropriately.en_US
dc.format.extent563814 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleA riccati equation approach to the singular LQG problemen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMechanical Engineeringen_US
dc.subject.hlbsecondlevelIndustrial and Operations Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Aerospace Engineering, The University of Michigan, Ann Arbor, MI 48109-2140, U.S.A.en_US
dc.contributor.affiliationotherDepartment of Mechanical and Aerospace Engineering, Florida Institute of Technology, Melbourne, FL, U.S.A.; Dept. of Mechanical Engineering, The Ohio State University, 206 West 18th Avenue Columbus, OH, USA.en_US
dc.contributor.affiliationotherDepartment of Mechanical and Aerospace Engineering, Florida Institute of Technology, Melbourne, FL 32902, U.S.A.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/30823/1/0000485.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0005-1098(93)90073-3en_US
dc.identifier.sourceAutomaticaen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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