In constructing multiprocessor-based distributed process control syste
ms, one approach is to use low-end processors to carry out direct cont
rol tasks at the local layer, while leaving more sophisticated tasks f
or high-end processors at the supervisory layer. For such a system arc
hitecture, reducing the data transmission on the communication link is
a challenging problem. Hung and Lefkowitz proposed a data aggregation
algorithm for compressing the original input/output data at the local
layer before passing them to the supervisory layer. At the supervisor
y layer, however, there is a lack of an effective algorithm to perform
the parameter estimation task based on the aggregated data. This pape
r describes a method which significantly improves the effectiveness of
this task. Systems under control are assumed to be linear with distin
ct eigenvalues. Simulation results are included.