Overview
- Describes the use of linear algebra based control algorithms (LABC) emphasizing their ease to use in various domains
- Synthesizes and generalizes the LABC, delivering realistic applications examples with additive uncertainty and time delay
- Presents an alternative perspective of control systems theories
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Table of contents (8 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book summarizes the application of linear algebra-based controllers (LABC) for trajectory tracking for practitioners and students across a range of engineering disciplines. It clarifies the necessary steps to apply this straight-forward technique to a non-linear multivariable system, dealing with continuous or discrete time models, and outlines the steps to implement such controllers. In this book, the authors present an approach of the trajectory tracking problem in systems with dead time and in the presence of additive uncertainties and environmental disturbances. Examples of applications of LABC to systems in real operating conditions (mobile robots, marine vessels, quadrotor and pvtol aircraft, chemical reactors and First Order Plus Dead Time systems) illustrate the controller design in such a way that the reader attains an understanding of LABC.
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Bibliographic Information
Book Title: Linear Algebra Based Controllers
Book Subtitle: Design and Applications
Authors: Gustavo Scaglia, Mario Emanuel Serrano, Pedro Albertos
DOI: https://doi.org/10.1007/978-3-030-42818-1
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-42817-4Published: 02 June 2020
Softcover ISBN: 978-3-030-42820-4Published: 02 June 2021
eBook ISBN: 978-3-030-42818-1Published: 01 June 2020
Edition Number: 1
Number of Pages: XV, 147
Number of Illustrations: 26 b/w illustrations, 41 illustrations in colour
Topics: Robotics and Automation, Control and Systems Theory, Mechatronics, Linear Algebra, Linear and Multilinear Algebras, Matrix Theory