9783737612418 - distributed model predictive control with uncertain communication di hahn, jannik (3 risultati)
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Da: preigu, Osnabrück, Germaniapreigu
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EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Distributed Model Predictive Control with Uncertain Communication | DE | Jannik Hahn | Taschenbuch | Englisch | kassel university press | EAN 9783737612418 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This thesis investigates model predictive control for distributed systems. To achieve a common task, all subsystems compute and share local predictions with their neighbors. Due to unreliable communication, shared data might be out…dated, and uncertain predictions must be used for planning. The proposed control strategies explicitly account for both network-induced and local uncertainties, considering bounded disturbances in a robust control framework and stochastic models within a chance-constrained MPC setting. In addition, the strategies incorporate predictions of the communication network itself to improve the overall system performance. Both schemes ensure recursive feasibility and closed-loop stability by using suitable terminal sets and constraints. Simulations validate constraint satisfaction and performance improvements. 200 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
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EUR 61,35 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This thesis investigates model predictive control for distributed systems. To achieve a common task, all subsystems compute and share local predictions with their neighbors. Due to unreliable communication, shared data might be outdated…, and uncertain predictions must be used for planning. The proposed control strategies explicitly account for both network-induced and local uncertainties, considering bounded disturbances in a robust control framework and stochastic models within a chance-constrained MPC setting. In addition, the strategies incorporate predictions of the communication network itself to improve the overall system performance. Both schemes ensure recursive feasibility and closed-loop stability by using suitable terminal sets and constraints. Simulations validate constraint satisfaction and performance improvements.
