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Filtering theory : with applications to fault detection, isolation, and estimation

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Cover of 'Filtering theory : with applications to fault detection, isolation, and estimation'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Preliminaries
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    Chapter 3 A special coordinate basis (SCB) of linear multivariable systems
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    Chapter 4 Algebraic Riccati equations and matrix inequalities
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    Chapter 5 Exact disturbance decoupling via state and full information feedback
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    Chapter 6 Almost disturbance decoupling via state and full information feedback
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    Chapter 7 Exact input-decoupling filters
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    Chapter 8 Almost input-decoupled filtering under white noise input
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    Chapter 9 Almost input-decoupled filtering without statistical assumptions on input
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    Chapter 10 Optimally (suboptimally) input-decoupling filtering under white noise input— H 2 filtering
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    Chapter 11 Optimally (suboptimally) input-decoupled filtering without statistical information on the input- H ∞ filtering
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    Chapter 12 Generalized H 2 suboptimally input-decoupled filtering
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    Chapter 13 Generalized H ∞ suboptimally input-decoupled filtering
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    Chapter 14 Fault detection, isolation, and estimation—exact or almost fault estimation
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    Chapter 15 Fault detection, isolation, and estimation—optimal fault estimation
Attention for Chapter 11: Optimally (suboptimally) input-decoupled filtering without statistical information on the input- H ∞ filtering
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