Observability and Redundancy in Process Data Estimation

By analogy to the development for dynamic systems, concepts of observability and redundancy may be developed with respect to a steady state system. These concepts differ from their counterparts for dynamic systems in that they can be used to characterize individual variables and local behavior as well as system and global behavior. Relations between local observability, global observability, calculability and redundancy are established and explored in this paper. It is shown that these concepts are useful in characterizing the performance of process data estimators with regard to bias and uniqueness of an estimate, convergence of estimation procedures and the feasibility and implications of problem decomposition.