This work unifies the partitioned adaptive estimators for stochastic systems and applies them to other estimation and control problems. The techniques used are not restricted to lumped-parameter systems with unknown constant parameters, but serve as a starting point for more complicated problems. These include abruptly changing parameters such as Markov jump and distributed parameter systems. Some useful background material is provided in the appendices and there is also a summary of recent work.
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Focused on the partitioned adaptive estimators for stochastic systems, this volume unifies basic theories in continuous-time and/or discrete-time linear dynamic systems and applies them to other estimation or control problems.
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