# Linear Optimal Control: H2 and H[infinity] Methods

Addison Wesley Longman, 1999 - Technology & Engineering - 462 pages

Linear Optimal Control: H2 and Ha Methods is a reader-friendly book that features recent research results on robustness, Ha control, and ...m- synthesis. Linear Optimal Control combines these new results with previous work on optimal control to form a complete picture of control system design and analysis.
A comprehensive book, Linear Optimal Control covers the analysis of control systems, H2 (linear quadratic Gaussian), and Ha to a degree not found in many similar books. Its logical organization and its focus on establishing a solid grounding in the basics be fore tackling mathematical subtleties make Linear Optimal Control an ideal learning tool.

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A comprehensive book, Linear Optimal Control covers the analysis of control systems, H2 (linear quadratic Gaussian), and to a degree not found in many texts. Its logical organization and its focus on establishing a solid grounding in the basics before tackling mathematical subtleties make Linear Optimal Control an ideal teaching text. The book's structure also makes it suitable for two-semester, one-semester, and two-quarter courses, as well as for professional use.

Features:

• Provides computer projects in each chapter to challenge readers with "what if" questions concerning the choice of cost functions and specifications.
• Simplifies results and derivations by treating special cases whenever possible without compromising the clarity of the results and methods.
• Familiarizes readers with the use of CAD tools for robust optimal controller design; software use is integrated throughout the book, and is included in almost every example.
• Offers a case study that compares the LQG and the u-synthesis design methodologies and provides guidelines on when to apply which method.
• Presents LQG and control within a common framework uses variational methods for both solutions.
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Very good book

### About the author (1999)

Jeffrey B. Burl is a Professor of Electrical Engineering at Michigan Technological University, where he is conducting research in several areas including image-based control systems for aerospace vehicles, automotive control, and robust multivariable control theory and applications. He has worked on the control of the international space station, missile autopilot design, and numerous other control projects. He is currently working on collision avoidance for general aviation. Dr. Burl has published papers in the IEEE Transactions on Signal Processing, the AIAA Journal of Guidance, Control, and Dynamics, and other journals. He is currently an Associate Editor for the International Journal of Modeling and Simulation, and a Senior Member of the IEEE and the AIAA.