Description
Linear Systems: Non-Fragile Control and Filtering presents the latest research results and a systematic approach to designing non-fragile controllers and filters for linear systems. The authors combine the algebraic Riccati technique, the linear matrix inequality (LMI) technique, and the sensitivity analysis method to establish a set of new non-fragile (insensitive) control methods. This proposed method can optimize the closed-loop system performance and make the designed controllers or filters tolerant of coefficient variations in controller or filter gain matrices.
A Systematic Approach to Designing Non-Fragile Controllers and Filters for Linear Systems
The text begins with developments and main research methods in non-fragile control. It then systematically presents novel methods for non-fragile control and filtering of linear systems with respect to additive/multiplicative controller/filter gain uncertainties. The book introduces the algebraic Riccati equation technique to solve additive/multiplicative norm-bounded controller/filter gain uncertainty, and proposes a structured vertex separator to deal with the numerical problem resulting from interval-bounded coefficient variations. It also explains how to design insensitive controllers and filters in the framework of coefficient sensitivity theory. Throughout, the book includes numerical examples to demonstrate the effectiveness of the proposed design methods.
More Effective Design Methods for Non-Fragile Controllers and Filters
The design and analysis tools described will help readers to better understand and analyze parameter uncertainties and to design more effective non-fragile controllers and filters. Providing a coherent approach, this book is a valuable reference for researchers, graduate students, and anyone who wants to explore the area of non-fragile control and filtering.
Table of Contents
Introduction
Preliminaries
Delta Operator Definition
H∞ Performance Index
Operations on Systems
Some Other Definitions and Lemmas
Non-Fragile State Feedback Control with Norm-Bounded Gain Uncertainty
Introduction
Problem Statement
Non-Fragile Guaranteed Cost Controller Design
Example
Conclusion
Non-Fragile Dynamic Output Feedback Control with Norm-Bounded Gain Uncertainty
Introduction
Problem Statement
Non-Fragile H∞ Dynamic Output Feedback Controller Design
Example
Conclusion
Robust Non-Fragile Kalman Filtering with Norm-Bounded Gain Uncertainty
Introduction
Problem Statement
Robust Non-Fragile Filter Design
Example
Conclusion
Non-Fragile Output Feedback Control with Interval-Bounded Coefficient Variations
Introduction
Non-Fragile H∞ Controller Design for Discrete-Time Systems
Non-Fragile H∞ Controller Design for Continuous-Time Systems
Non-Fragile H∞ Controllers Design with Sparse Structures
Conclusion
Non-Fragile H∞ Filtering with Interval-Bounded Coefficient Variations
Introduction
Non-Fragile H∞ Filtering for Discrete-Time Systems
Non-Fragile H∞ Filter Design for Linear Continuous-Time Systems
Sparse Structured H∞ Filter Design
Conclusion
Insensitive H∞ Filtering of Continuous-Time Systems
Introduction
Problem Statement
Insensitive H∞ Filter Design
Computation of Robust H∞ Performance Index
Comparison with the Existing Design Method
Example
Conclusion
Insensitive H∞ Filtering of Delta Operator Systems
Introduction
Problem Statement
Insensitive H∞ Filter Design
Example
Conclusion
Insensitive H∞ Output Tracking Control
Introduction
Problem Statement
Insensitive H∞ Tracking Control Design
Example
Conclusion
Insensitive H∞ Dynamic Output Feedback Control
Introduction
Problem Statement
Insensitive H∞ Controller Design
Example
Conclusion
Bibliography
Index
