Adaptive Control of Hyperbolic Pdes

ISBN-13: 9783030058784 / Angielski / Twarda / 2019 / 478 str.

Henrik Anfinsen; Ole Morten Aamo

Opis

MATLAB files for simulations

Spis treści

Part I: Background.- Chapter 1. Background.- Part II: Scalar systems.- Chapter 2. Introduction.- Chapter 3. Non-adaptive schemes.- Chapter 4. Adaptive state-feedback controller.- Chapter 5. Adaptive output-feedback controller.- Chapter 6. Model reference adaptive control.- Part III: 2 × 2-systems.- Chapter 7. Introduction.- Chapter 8. Non-adaptive schemes.- Chapter 9. Adaptive state feedback controllers.- Chapter 10. Adaptive output-feedback: uncertain boundary condition.- Chapter 11. Adaptive output-feedback: uncertain in-domain parameters.- Chapter 12. Model reference adaptive control.- Part IV: n + 1-systems.- Chapter 13. Introduction.- Chapter 14. Non-adaptive schemes.- Chapter 15. Adaptive state-feedback controller.- Chapter 16. Adaptive output-feedback: uncertain boundary condition.- Chapter 17. Model reference adaptive control.- Part V: n + m-systems.- Chapter 18. Introduction.- Chapter 19. Non-adaptive schemes.- Chapter 20. Adaptive output-feedback: uncertain boundary condition.- References.

O autorze

Henrik Anfinsen received his M.Sc. and Ph.D. degrees from the Department of Engineering Cybernetics at the Norwegian University of Science and Technology, Trondheim, Norway, in 2013 and 2018, respectively. As a researcher at NTNU, he co-authored more than forty papers on non-adaptive and adaptive control of linear hyperbolic PDEs.

Ole Morten Aamo received the M.Sc. and Ph.D. degrees in engineering cybernetics from the Norwegian University of Science and Technology (NTNU), Trondheim, Norway, in 1992 and 2002, respectively. He was a reasearch scientist with the Environmental Modelling Section of SINTEF from 1993 to 1997, a post doc researcher at NTNU from 2002 to 2006, and has been a Professor with NTNU since 2006. He is a co-author of the book Flow Control by Feedback (Springer 2003), and has co-authored about 200 scientific papers. His main research interests include the estimation and control of distributed parameter systems with special emphasis on control of fluid flows.

Blurb

Adaptive Control of Linear Hyperbolic PDEs provides a comprehensive treatment of adaptive control of linear hyperbolic systems, using the backstepping method. It develops adaptive control strategies for different combinations of measurements and actuators, as well as for a range of different combinations of parameter uncertainty. The book treats boundary control of systems of hyperbolic partial differential equations (PDEs) with uncertain parameters. 

The authors develop designs for single equations, as well as any number of coupled equations. The designs are accompanied by mathematical proofs, which allow the reader to gain insight into the technical challenges associated with adaptive control of hyperbolic PDEs, and to get an overview of problems that are still open for further research. Although stabilization of unstable systems by boundary control and boundary sensing are the particular focus, state-feedback designs are also presented. The book also includes simulation examples with implementational details and graphical displays, to give readers an insight into the performance of the proposed control algorithms, as well as the computational details involved. A library of MATLAB® code supplies ready-to-use implementations of the control and estimation algorithms developed in the book, allowing readers to tailor controllers for cases of their particular interest with little effort. These implementations can be used for many different applications, including pipe flows, traffic flow, electrical power lines, and more.

Adaptive Control of Linear Hyperbolic PDEs is of value to researchers and practitioners in applied mathematics, engineering and physics; it contains a rich set of adaptive control designs, including mathematical proofs and simulation demonstrations. The book is also of interest to students looking to expand their knowledge of hyperbolic PDEs.