Model Predictive Control 3_2 - short output horizon in GPC
Listen now
Description
Gives a number of illustrations of GPC predictions with short output horizons and demonstrates how the associated predictions are often very poor which in turn suggests the GPC optimisation is ill-posed and not to be trusted.
More Episodes
Looks at choices of input horizon equal to 2 and demonstrates that for many cases this is not sufficiently flexible to give good predictions and thus cannot lead to an expectation of good closed-loop behaviour.
Published 04/28/14
Demonstrates that the input weighting parameter has a limited range of efficacy which is linked to the horizons. Moreover, it is shown that the required horizons for a well-posed optimisation are strongly linked to the choice of this weighting. Also demonstrates that the parameter must be used...
Published 04/28/14
Gives a number of illustrations of GPC predictions with long output horizons and demonstrates how the associated predictions can be very good and thus lead to a GPC optimisation which is well-posed and can be be trusted. However, also shows this insight does not necessarily apply to systems with...
Published 04/28/14