{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/80925"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/80925","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Optimal Estimation and Control Under Communication Network Constraints","abstract":"Several new optimal estimation and control problems are introduced with hard constraints on the availability of information or on the number of times the information and/or control may be available. We are motivated by applications in networked control systems, but most of the results derived here can equally be applied to other areas of decision and control theory, such as economic forecasting or inventory control. Information plays a critical role in determining the optimal control and/or estimation laws for these new problems. The problems are formulated in a team decision theory setting, and dynamic programming type arguments are used to derive the optimal decision policies. Theoretical results and algorithms obtained are demonstrated through numerical simulations in Matlab.","abstract_html":"Several new optimal estimation and control problems are introduced with hard constraints on the availability of information or on the number of times the information and/or control may be available. We are motivated by applications in networked control systems, but most of the results derived here can equally be applied to other areas of decision and control theory, such as economic forecasting or inventory control. Information plays a critical role in determining the optimal control and/or estimation laws for these new problems. The problems are formulated in a team decision theory setting, and dynamic programming type arguments are used to derive the optimal decision policies. 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We are motivated by applications in networked control systems, but most of the results derived here can equally be applied to other areas of decision and control theory, such as economic forecasting or inventory control. Information plays a critical role in determining the optimal control and/or estimation laws for these new problems. The problems are formulated in a team decision theory setting, and dynamic programming type arguments are used to derive the optimal decision policies. Theoretical results and algorithms obtained are demonstrated through numerical simulations in Matlab.","Made available in DSpace on 2015-09-25T20:08:52Z (GMT). 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