Linear-quadratic controls in risk-averse decision making : performance-measure statistics and control decision pptimization

Linear-Quadratic Controls in Risk-Averse Decision Making   cuts across control engineering (control feedback and decision optimization) and statistics (post-design performance analysis) with a common theme: reliability increase seen from the responsive angle of incorporating and engineering multi-le...

Disgrifiad llawn

Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Prif Awdur: Pham, Khanh D., 19..-
Fformat: Livre numérique
Iaith:Anglais
Cyhoeddwyd: New York, NY : Springer New York 2013.
Cham : Springer Nature
Cyfres:SpringerBriefs in Optimization
Mynediad Ar-lein:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Nodyn: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Linear-Quadratic Controls in Risk-Averse Decision Making, Texte imprimé, 9781461450788
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245 1 0 |a Linear-quadratic controls in risk-averse decision making :  |b performance-measure statistics and control decision pptimization   |c by Khanh D. Pham. 
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520 |a Linear-Quadratic Controls in Risk-Averse Decision Making   cuts across control engineering (control feedback and decision optimization) and statistics (post-design performance analysis) with a common theme: reliability increase seen from the responsive angle of incorporating and engineering multi-level performance robustness beyond the long-run average performance into control feedback design and decision making and complex dynamic systems from the start. This monograph provides a complete description of statistical optimal control (also known as cost-cumulant control) theory. In control problems and topics, emphasis is primarily placed on major developments attained and explicit connections between mathematical statistics of performance appraisals and decision and control optimization. Chapter summaries shed light on the relevance of developed results, which makes this monograph suitable for graduate-level lectures in applied mathematics and electrical engineering with systems-theoretic concentration, elective study or a reference for interested readers, researchers, and graduate students who are interested in theoretical constructs and design principles for stochastic controlled systems.   
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