Modern Control: State-Space Analysis and Design Methods
Seiten
2020
McGraw-Hill Education (Verlag)
978-1-260-45924-1 (ISBN)
McGraw-Hill Education (Verlag)
978-1-260-45924-1 (ISBN)
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.
Apply a state-space approach to modern control system analysis and design
Written by an expert in the field, this concise textbook offers hands-on coverage of modern control system engineering. Modern Control: State-Space Analysis and Design Methods features start-to-finish design projects as well as online snippets of MATLAB code with simulations. The essential mathematics are presented along with fully worked-out examples in gradually increasing degrees of difficulty. Readers will receive “just-in-time” math background from a comprehensive appendix and get step-by-step descriptions of the latest analysis and design techniques.
Coverage includes:
• An introduction to control systems
• State-space representations
• Pole placement via state feedback
• State estimators (observers)
• Non-minimal canonical forms
• Linearization
• Lyapunov stability
• Linear quadratic regulators (LQR)
• Symmetric root locus (SRL)
• Kalman filter
• Linear quadratic gaussian control (LQG)
Apply a state-space approach to modern control system analysis and design
Written by an expert in the field, this concise textbook offers hands-on coverage of modern control system engineering. Modern Control: State-Space Analysis and Design Methods features start-to-finish design projects as well as online snippets of MATLAB code with simulations. The essential mathematics are presented along with fully worked-out examples in gradually increasing degrees of difficulty. Readers will receive “just-in-time” math background from a comprehensive appendix and get step-by-step descriptions of the latest analysis and design techniques.
Coverage includes:
• An introduction to control systems
• State-space representations
• Pole placement via state feedback
• State estimators (observers)
• Non-minimal canonical forms
• Linearization
• Lyapunov stability
• Linear quadratic regulators (LQR)
• Symmetric root locus (SRL)
• Kalman filter
• Linear quadratic gaussian control (LQG)
Dr. Arie Nakhmani (M.Sc. in Robust Control, Ph.D. in Computer Vision), is Associate Professor of Electrical and Computer Engineering, Associate Scientist in the Comprehensive Cancer Center, and director of ANRY lab at the University of Alabama at Birmingham. He is the author of over 50 peer-reviewed research articles and book chapters on robust control, machine learning, signal and image analysis.
Erscheinungsdatum | 28.04.2020 |
---|---|
Zusatzinfo | 50 Illustrations, unspecified |
Verlagsort | OH |
Sprache | englisch |
Maße | 170 x 234 mm |
Gewicht | 479 g |
Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
Technik ► Elektrotechnik / Energietechnik | |
ISBN-10 | 1-260-45924-1 / 1260459241 |
ISBN-13 | 978-1-260-45924-1 / 9781260459241 |
Zustand | Neuware |
Haben Sie eine Frage zum Produkt? |
Mehr entdecken
aus dem Bereich
aus dem Bereich
Grundlagen – Anwendungen – Perspektiven
Buch | Softcover (2022)
Springer Vieweg (Verlag)
34,99 €
Eine Einführung in die Systemtheorie
Buch | Softcover (2022)
UTB (Verlag)
25,00 €