摘要：AbstractUncertainty is inherent in bioprocess modelling and control. Typically, uncertainties are handled using either the stochastic approach or the robust approach. Recently, the risk-averse approach, i.e., an interpolation between the stochastic and worst-case robust approach is gaining popularity. Risk-averse formulations are very useful in avoiding conservative solutions while still handling high-effect, low-probability events. In the bioreactor case considered in this paper, one such high effect low probability event is wash off caused by high feed rate or low inlet substrate concentration. A risk-averse, risk-constrained model predictive control formulation is proposed in this paper. The dynamic optimisation problem to be solved at every measurement instance is formulated using AV@R type risk objective. Similarly, probabilistic chance constraints are approximated by an AV@R-type risk constraints. The problem is then solved using the conic duality of the risk measure and an epigraphical decomposition of the nested multistage problem.
关键词：Keywordsuncertaintyrisk-averse optimisationmodel predictive controlbioreactor control
