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We present a Monte Carlo simulation framework for analysing the risk involvedin deploying real-time control systems in safety-critical applications, as wellas an algorithm design technique allowing one (in certain situations) torobustify a control algorithm. Both approaches are very general and agnostic tothe initial control algorithm. We present examples showing that thesetechniques can be used to analyse the reliability of implementations ofnon-linear model predictive control algorithms.

A risk analysis framework for real-time control systems