The use of a process model within a controller to obtain improved cont
rol is described. The approach is to choose the process variables most
suitable from a control standpoint for use as measured quantities and
, where these are not available as actual measurements, to predict the
m using the model. Key features of this work are the use of a general
nonlinear model and its augmentation by an output-error feedback loop
for model parameter adjustment. The first enables a full, rigorous mod
el to be used; if required this can be the same model used for design
purposes. The second makes the technique robust to model-process misma
tch. The method is illustrated by means of a very simple nonlinear exa
mple, and the results of its application to a more complex system are
reported.