Bubnicki Modern Control Theory

1. Auflage 2005
ISBN: 978-3-540-28087-3
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 423 Seiten, eBook

The main aim of this book is to present a unified, systematic description of basic and advanced problems, methods and algorithms of the modern c- trol theory considered as a foundation for the design of computer control and management systems. The scope of the book differs considerably from the topics of classical traditional control theory mainly oriented to the needs of automatic control of technical devices and technological pr- esses. Taking into account a variety of new applications, the book presents a compact and uniform description containing traditional analysis and - timization problems for control systems as well as control problems with non-probabilistic models of uncertainty, problems of learning, intelligent, knowledge-based and operation systems – important for applications in the control of manufacturing processes, in the project management and in the control of computer systems. Into the uniform framework of the book, original ideas and results based on the author’s works concerning uncertain and intelligent knowledge-based control systems, applications of uncertain variables and the control of complexes of operations have been included. The material presented in the book is self-contained. Using the text does not require any earlier knowledge on the control science. The presentation requires only a basic knowledge of linear algebra, differential equations and probability theory. I hope that the book can be useful for students, - searches and all readers working in the field of control and information science and engineering.

Zielgruppe

Research

Autoren/Hrsg.

Bubnicki, Zdzislaw

Inhaltsverzeichnis

General Characteristic of Control Systems.- Formal Models of Control Systems.- Control for the Given State (the Given Output).- Optimal Control with Complete Information on the Plant.- Parametric Optimization.- Application of Relational Description of Uncertainty.- Application of Probabilistic Descriptions of Uncertainty.- Uncertain Variables and Their Applications.- Fuzzy Variables, Analogies and Soft Variables.- Control in Closed-loop System. Stability.- Adaptive and Learning Control Systems.- Intelligent and Complex Control Systems.- Control of Operation Systems.