Clustering-based average state observer design for large-scale network systems

This paper addresses the aggregated monitoring problem for large-scale network systems with a few dedicated sensors. Full state estimation of such is often infeasible due to unobservability and/or computational infeasibility; therefore, through clustering and aggregation, tractable representation system, called projected obtained designing minimum-order average observer. observer estimates states clusters, which are identified under explicit consideration error. Moreover, given clustering, proposed design algorithm exploits structure error dynamics achieve tractability. Simulations show that computation significantly faster than usual H2/H∞ techniques. On other hand, compromise on characteristics shown be marginal.