{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T13:37:30Z","timestamp":1762522650000},"reference-count":26,"publisher":"Walter de Gruyter GmbH","issue":"9","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["SPP1914"],"award-info":[{"award-number":["SPP1914"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,9,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This paper proposes a scheme of model predictive control for single-loop networked control system (NCS) with probabilistically modeled communication channel and disturbances. Uncertainties of the communication network are projected onto a tailored probability for the satisfaction of state and input constraints. The proposed receding horizon control scheme uses a probabilistic terminal state and set to establish a balance between control performance and state probability distribution, while satisfying the given constraints. In addition to describing the control approach, its properties are discussed, and it is illustrated by an example.<\/jats:p>","DOI":"10.1515\/auto-2021-0033","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T21:00:36Z","timestamp":1631134836000},"page":"771-781","source":"Crossref","is-referenced-by-count":2,"title":["Constrained stochastic predictive control of linear systems with uncertain communication"],"prefix":"10.1515","volume":"69","author":[{"given":"Jannik","family":"Hahn","sequence":"first","affiliation":[{"name":"Control and System Theory, Dept. of Electrical Engineering and Computer Science , University of Kassel , Kassel , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olaf","family":"Stursberg","sequence":"additional","affiliation":[{"name":"Control and System Theory, Dept. of Electrical Engineering and Computer Science , University of Kassel , Kassel , Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2021,9,9]]},"reference":[{"key":"2023033110360518556_j_auto-2021-0033_ref_001","doi-asserted-by":"crossref","unstructured":"J.\u2009P. Hespanha, P. Naghshtabrizi and Y. Xu, \u201cA survey of recent results in networked control systems,\u201d Proc. of the IEEE, vol.\u200995, no.\u20091, pp.\u2009138\u2013162, 2007.","DOI":"10.1109\/JPROC.2006.887288"},{"key":"2023033110360518556_j_auto-2021-0033_ref_002","doi-asserted-by":"crossref","unstructured":"I. Akyildiz, W. Su, Y. Sankarasubramaniam, et al., \u201cWireless sensor networks: A survey,\u201d Computer Networks, vol.\u200938, no.\u20094, pp.\u2009393\u2013422, 2002.","DOI":"10.1016\/S1389-1286(01)00302-4"},{"key":"2023033110360518556_j_auto-2021-0033_ref_003","doi-asserted-by":"crossref","unstructured":"E.\u2009A. Lee, \u201cCyber physical systems: Design challenges,\u201d in 11th IEEE Int. Symp. on Object and Component-oriented Real-time Distributed Computing, IEEE, 2008, pp.\u2009363\u2013369.","DOI":"10.1109\/ISORC.2008.25"},{"key":"2023033110360518556_j_auto-2021-0033_ref_004","doi-asserted-by":"crossref","unstructured":"D. Gro\u00df and O. 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Esfanjani, \u201cDistributed predictive formation control of networked mobile robots subject to communication delay,\u201d Robotics and Autonomous Systems, vol.\u200991, pp.\u2009194\u2013207, 2017.","DOI":"10.1016\/j.robot.2017.01.005"},{"key":"2023033110360518556_j_auto-2021-0033_ref_007","doi-asserted-by":"crossref","unstructured":"J. Hahn, R. Schoeffauer, G. Wunder, et al., \u201cDistributed MPC with prediction of time-varying communication delay,\u201d IFAC-PapersOnLine, vol.\u200951, no.\u200923, pp.\u2009224\u2013229, 2018.","DOI":"10.1016\/j.ifacol.2018.12.039"},{"key":"2023033110360518556_j_auto-2021-0033_ref_008","doi-asserted-by":"crossref","unstructured":"J. Hahn and O. 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Morozan, \u201cOptimal stationary control for dynamic systems with Markov perturbations,\u201d Stochastic Analysis and Applications, vol.\u20091, no.\u20093, pp.\u2009299\u2013325, 1983.","DOI":"10.1080\/07362998308809016"},{"key":"2023033110360518556_j_auto-2021-0033_ref_024","doi-asserted-by":"crossref","unstructured":"M. Cannon, B. Kouvaritakis and X. Wu, \u201cProbabilistic constrained MPC for multiplicative and additive stochastic uncertainty,\u201d IEEE Trans. on Automatic Control, vol.\u200954, no.\u20097, pp.\u20091626\u20131632, 2009.","DOI":"10.1109\/TAC.2009.2017970"},{"key":"2023033110360518556_j_auto-2021-0033_ref_025","doi-asserted-by":"crossref","unstructured":"L. Hewing and M.\u2009N. 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