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Variance-Constrained Multi-Objective Stochastic Control and Filtering

Author: Lifeng Ma; Zidong Wang; Yuming Bo
Publisher: Hoboken : Wiley, 2015.
Series: Wiley series in dynamics and control of electromechanical systems.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
Unifies existing and emerging concepts concerning multi-objective control and stochastic control with engineering-oriented phenomena Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance Includes case studies of several nonlinear stochastic systems Investigates the phenomena of incomplete information,  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Ma, Lifeng
Variance-Constrained Multi-Objective Stochastic Control and Filtering
Hoboken : Wiley,c2015
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Lifeng Ma; Zidong Wang; Yuming Bo
ISBN: 9781118929476 1118929470
OCLC Number: 908519976
Notes: Description based upon print version of record.
10.4 Numerical Example
Description: 1 online resource (320 p.)
Contents: Cover; Title Page; Copyright; Contents; Preface; Series Preface; Acknowledgements; List of Abbreviations; List of Figures; Chapter 1 Introduction; 1.1 Analysis and Synthesis of Nonlinear Stochastic Systems; 1.1.1 Nonlinear Systems; 1.1.2 Stochastic Systems; 1.2 Multi-Objective Control and Filtering with Variance Constraints; 1.2.1 Covariance Control Theory; 1.2.2 Multiple Performance Requirements; 1.2.3 Design Techniques for Nonlinear Stochastic Systems with Variance Constraints; 1.2.4 A Special Case of Multi-Objective Design: Mixed H2/H∞ Control/Filtering; 1.3 Outline Chapter 2 Robust H∞ Control with Variance Constraints2.1 Problem Formulation; 2.2 Stability, H∞ Performance, and Variance Analysis; 2.2.1 Stability and H∞ Performance Analysis; 2.2.2 Variance Analysis; 2.3 Robust Controller Design; 2.4 Numerical Example; 2.5 Summary; Chapter 3 Robust Mixed H2/H∞ Filtering; 3.1 System Description and Problem Formulation; 3.2 Algebraic Characterizations for Robust H2/H∞ Filtering; 3.2.1 Robust H2 Filtering; 3.2.2 Robust H∞ Filtering; 3.3 Robust H2/H∞ Filter Design Techniques; 3.4 An Illustrative Example; 3.5 Summary Chapter 4 Robust Variance-Constrained Filtering with Missing Measurements4.1 Problem Formulation; 4.2 Stability and Variance Analysis; 4.3 Robust Filter Design; 4.4 Numerical Example; 4.5 Summary; Chapter 5 Robust Fault-Tolerant Control with Variance Constraints; 5.1 Problem Formulation; 5.2 Stability and Variance Analysis; 5.3 Robust Controller Design; 5.4 Numerical Example; 5.5 Summary; Chapter 6 Robust H2 Sliding Mode Control; 6.1 The System Model; 6.2 Robust H2 Sliding Mode Control; 6.2.1 Switching Surface; 6.2.2 Performances of the Sliding Motion; 6.2.3 Computational Algorithm 6.3 Sliding Mode Controller6.4 Numerical Example; 6.5 Summary; Chapter 7 Variance-Constrained Dissipative Control with Degraded Measurements; 7.1 Problem Formulation; 7.2 Stability, Dissipativity, and Variance Analysis; 7.3 Observer-Based Controller Design; 7.3.1 Solvability of the Multi-Objective Control Problem; 7.3.2 Computational Algorithm; 7.4 Numerical Example; 7.5 Summary; Chapter 8 Variance-Constrained H∞ Control with Multiplicative Noises; 8.1 Problem Formulation; 8.2 Stability, H∞ Performance, and Variance Analysis; 8.2.1 Stability; 8.2.2 H∞ Performance; 8.2.3 Variance Analysis 8.3 Robust State Feedback Controller Design8.4 Numerical Example; 8.5 Summary; Chapter 9 Robust H∞ Control with Variance Constraints: the Finite-Horizon Case; 9.1 Problem Formulation; 9.2 Performance Analysis; 9.2.1 H∞ Performance; 9.2.2 Variance Analysis; 9.3 Robust Finite-Horizon Controller Design; 9.4 Numerical Example; 9.5 Summary; Chapter 10 Error Variance-Constrained H∞ Filtering with Degraded Measurements: The Finite-Horizon Case; 10.1 Problem Formulation; 10.2 Performance Analysis; 10.2.1 H∞ Performance Analysis; 10.2.2 System Covariance Analysis; 10.3 Robust Filter Design
Series Title: Wiley series in dynamics and control of electromechanical systems.

Abstract:

Unifies existing and emerging concepts concerning multi-objective control and stochastic control with engineering-oriented phenomena Establishes a unified theoretical framework for control and filtering problems for a class of discrete-time nonlinear stochastic systems with consideration to performance Includes case studies of several nonlinear stochastic systems Investigates the phenomena of incomplete information, including missing/degraded measurements, actuator failures and sensor saturations Considers both time-invariant systems and time-varying systems Exploits newly developed technique.

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