Adaptive Estimation and Control

Adaptive Estimation and Control : The Partitioning Approach

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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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Product details

  • Hardback | 500 pages
  • 154 x 236 x 44.45mm | 996g
  • Prentice-Hall
  • Harlow, United Kingdom
  • English
  • references, index
  • 0130054224
  • 9780130054227

Table of contents

Review of Kalman filtering theory; structure and parameter adaptive estimation; asymptotic and convergence properties of partitioned adaptive systems; partitioning filter - probabilistic approach; partitioning estimators - scattering approach; pseudolinear partitioning filter and tracking motion analysis; two-stage bias correction estimators based on generalized partitioning filter; forward-pass fixed-interval smoother in discrete-time systems; multiple model adaptive filtering and control for Markovian jump system.
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