Harnessing Uncertainty for a Separation Principle in Direct Data-Driven Predictive Control

Model Predictive Control (MPC) is a powerful method for complex system regulation, but its reliance on an accurate model poses many limitations in real-world applications. Data-driven predictive control (DDPC) aims at overcoming this limitation, by relying on historical data to provide information o...

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Veröffentlicht in:	arXiv.org 2024-08
Hauptverfasser:	Chiuso, Alessandro, Fabris, Marco, Breschi, Valentina, mentin, Simone
Format:	Artikel
Sprache:	eng
Schlagworte:	Complex systems Noise control Optimization Predictive control Regularization
Online-Zugang:	Volltext
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