IMPROVED CONTROL USING DYNAMIC PROCESS MODELS

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.