This monograph presents a detailed and unified treatment of the
theory of reduced order systems. Covered topics include reduced
order modeling, reduced order estimation, reduced order control,
and the design of reduced order compensators for stochastic
systems. Special emphasis is placed on optimization using a
quadratic performance criterion. Both continuous and discrete time
linear dynamical systems are considered, and state space system
representation is used throughout the book. It provides a coherent
view of the recent theory of reduced order theory and its
applications including a wide range of application problems,
solutions and unresolved issues.
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