Introduction to Stochastic MPC

Abstract

Uncertainty forms an integral part of most control problems and earlier chapters discussed how MPC algorithms can be constructed in order to treat model uncertainty in a robust sense. One of the key features of robust MPC is that it requires constraints to be satisfied for all possible realizations of uncertainty. Thus each element of the set of values that can be assumed by an uncertain model parameter or disturbance input is treated with equal importance, and robust MPC does not discriminate between alternative realizations on the basis of their respective likelihood.