
Operator Splitting Methods in Control
now publishers Inc
1st Edition
Published on 15. August 2016
Book
Paperback/Softback
136 pages
978-1-68083-174-0 (ISBN)
Description
The significant progress that has been made in recent years both in hardware implementations and in numerical computing has rendered real-time optimization-based control a viable option when it comes to advanced industrial applications. More recently, the need for control of a process in the presence of a limited amount of hardware resources has triggered research in the direction of embedded optimization-based control.
Operator Splitting Methods in Control focuses on systems with linear dynamics, giving rise to convex control problems. It provides a comprehensive survey of a family of first order methods known as decomposition schemes or operator splitting methods and shows the behavior of such algorithms as solvers of control related convex problems from tens to a few hundreds of variables.
This compact survey gives the reader a state-of-the-art overview of the topic with examples of applications in aerospace and building control.
Operator Splitting Methods in Control focuses on systems with linear dynamics, giving rise to convex control problems. It provides a comprehensive survey of a family of first order methods known as decomposition schemes or operator splitting methods and shows the behavior of such algorithms as solvers of control related convex problems from tens to a few hundreds of variables.
This compact survey gives the reader a state-of-the-art overview of the topic with examples of applications in aerospace and building control.
More details
Series
Language
English
Place of publication
Hanover
United States
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 7 mm
Weight
202 gr
ISBN-13
978-1-68083-174-0 (9781680831740)
DOI
10.1561/2600000008
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Schweitzer Classification
Content
1. Introduction. 2. The Algorithms. 3. Convergence Results and Accelerated Variants. 4. Stepsize Selection and Preconditioning. 5. Numerical Linear Algebra. 6. Examples. 7. Summary. References.