LMI-Based Robustness Analysis in Uncertain Systems

Author:   Graziano Chesi
Publisher:   now publishers Inc
ISBN:  

9781638282983


Pages:   206
Publication Date:   07 February 2024
Format:   Paperback
Availability:   In Print   Availability explained
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LMI-Based Robustness Analysis in Uncertain Systems


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Overview

The study of uncertain systems has played a significant role throughout the history of control engineering due to unknown quantities often being present in the mathematical model of a plant. In this monograph the author provides a unified framework for the fundamental and challenging area of robustness analysis of uncertain systems, where even the most basic problem of establishing robust stability may be still present. This framework uses linear matrix inequalities (LMIs) to exploit polynomials that can be expressed as sums of squares of polynomials (SOS).The author guides the reader through the motivations for using the framework including considering various types of uncertainties; providing guarantees for robust stability and robust performance; requiring the solution of convex optimization problems; allowing for trade-off between conservatism and complexity; and concluding with a number of special case methods. This monograph can be used by researchers and students to understand the issues and use the numerical examples to identify the use of the framework in modern controls systems.

Full Product Details

Author:   Graziano Chesi
Publisher:   now publishers Inc
Imprint:   now publishers Inc
Weight:   0.297kg
ISBN:  

9781638282983


ISBN 10:   1638282986
Pages:   206
Publication Date:   07 February 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1. Introduction 2. Optimization with LMIs 3. Positive Matrix Polynomials 4. Models for Uncertain Systems 5. Robust Stability 6. Robust Performance 7. Conclusion Acknowledgements Appendices References

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