We propose to use chance constrained programming for process optimization and control under uncertainty. The stochastic property of the uncertainties is included in the problem formulation. The output constraints are to be ensured with a predefined confidence level. The problem is then transformed to an equivalent deterministic NLP problem. The solution of the problem has the feature of predict...
