Constraint-Tightening and Stability in Stochastic Model Predictive Control

Constraint tightening to non-conservatively guarantee recursive feasibility and stability in Stochastic Model Predictive Control is addressed. Stability and feasibility requirements are considered separately, highlighting the difference between existence of a solution and feasibility of a suitable,...

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Veröffentlicht in:	IEEE transactions on automatic control Jg. 62; H. 7; S. 3165 - 3177
Hauptverfasser:	Lorenzen, Matthias, Dabbene, Fabrizio, Tempo, Roberto, Allgower, Frank
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.07.2017
Schlagworte:	Asymptotic stability Chance constraints constrained control discrete-time stochastic systems Numerical stability Optimization Predictive control randomized algorithms receding horizon control Robustness stochastic model predictive control Stochastic processes Uncertainty
ISSN:	0018-9286, 1558-2523
Online-Zugang:	Volltext
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