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020 _a9783319656144
_9978-3-319-65614-4
024 7 _a10.1007/978-3-319-65614-4
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aGPFC
_2bicssc
072 7 _aTEC004000
_2bisacsh
072 7 _aTJFM
_2thema
082 0 4 _a629.8312
_223
082 0 4 _a003
_223
100 1 _aLeong, Alex S.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961427
245 1 0 _aOptimal Control of Energy Resources for State Estimation Over Wireless Channels
_h[electronic resource] /
_cby Alex S. Leong, Daniel E. Quevedo, Subhrakanti Dey.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aVII, 125 p. 38 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Control, Automation and Robotics,
_x2192-6794
505 0 _aIntroduction. - Optimal Power Allocation for Kalman Filtering over Fading Channels -- Optimal Transmission Scheduling for Event-Triggered Estimation -- Optimal Transmission Strategies for Remote State Estimation -- Remote State Estimation in Multi-Hop Networks -- Conclusion.
520 _aThis brief introduces wireless communications ideas and techniques into the study of networked control systems. It focuses on state estimation problems in which sensor measurements (or related quantities) are transmitted over wireless links to a central observer. Wireless communications techniques are used for energy resource management in order to improve the performance of the estimator when transmission occurs over packet dropping links, taking energy use into account explicitly in Kalman filtering and control. The brief allows a reduction in the conservatism of control designs by taking advantage of the assumed. The brief shows how energy-harvesting-based rechargeable batteries or storage devices can offer significant advantages in the deployment of large-scale wireless sensor and actuator networks by avoiding the cost-prohibitive task of battery replacement and allowing self-sustaining sensor to be operation. In contrast with research on energy harvesting largely focused on resource allocation for wireless communication systems design, this brief optimizes estimation objectives such as minimizing the expected estimation error covariance. The resulting power control problems are often stochastic control problems which take into account both system and channel dynamics. The authors show how to pose and solve such design problems using dynamic programming techniques. Researchers and graduate students studying networked control systems will find this brief a helpful source of new ideas and research approaches.
650 0 _aControl engineering.
_931970
650 0 _aApplication software.
_961428
650 0 _aTelecommunication.
_910437
650 1 4 _aControl and Systems Theory.
_931972
650 2 4 _aComputer and Information Systems Applications.
_961429
650 2 4 _aCommunications Engineering, Networks.
_931570
700 1 _aQuevedo, Daniel E.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961430
700 1 _aDey, Subhrakanti.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961431
710 2 _aSpringerLink (Online service)
_961432
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319656137
776 0 8 _iPrinted edition:
_z9783319656151
830 0 _aSpringerBriefs in Control, Automation and Robotics,
_x2192-6794
_961433
856 4 0 _uhttps://doi.org/10.1007/978-3-319-65614-4
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c80756
_d80756