A probabilistic validation approach for penalty function design in Stochastic Model Predictive Control

16 Mar 2020 Mammarella Martina Alamo Teodoro Lucia Sergio Dabbene Fabrizio

In this paper, we consider a stochastic Model Predictive Control able to account for effects of additive stochastic disturbance with unbounded support, and requiring no restrictive assumption on either independence nor Gaussianity. We revisit the rather classical approach based on penalty functions, with the aim of designing a control scheme that meets some given probabilistic specifications... (read more)

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