Robust Process Control by Dynamic Stochastic Programming
نویسنده
چکیده
Unnecessarily conservative behavior of standard process control techniques can be avoided by stochastic programming models when the distribution of random distur bances is known. In an earlier study we have investigated such an approach for tank level constraints of a distillation process. Here we address techniques that have accelerated the numerical solution of the large and expensive stochastic programs by a factor of six, and then present a refined optimization model for the same application.
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