On reducing data communication in multiprocessor-based distributed process control systems

A modern multiprocessor-based distributed process control system usually consists of at least two layers: a local DDC (direct digital control) layer, and a supervisory layer. Performance of such a system relies on effectiveness of the communication link that connects the two layers. To improve the efficiency of the communication link, one approach is to reduce the data communication between the layers. The first introduce a data aggregation algorithm which compresses the original input/output data at the local layer before passing them to the supervisory layer. A parameter estimation method is then discussed which allows the supervisory layer to perform a parameter estimation task based on the aggregated data it received. With this approach, the layer-to-layer data communication required by updating supervisory functions can be significantly reduced. Simulation results are included.