Latin Abstract :
In this paper the disturbance model,used by MPC algorithms to achieve offset-free control,is optimally designed to enhance the
robustness of single-model predictive controllers. The proposed methodology requires the off-line solution of a min-max optimization
problem in which the disturbance model is chosen to guarantee the best closed-loop performance in the worst case of plant in
a given uncertainty region. Application to a well-known ill-conditioned distillation column is presented to show that,for ill-conditioned
processes,the use of a disturbance model that adds the correction term to the process inputs guarantees a robust performance,
while the disturbance model that adds the correction term to the process outputs (used by industrial MPC algorithms) does
not.
