Functional Adaptive Control | An Intelligent Systems Approach

Simon G. Fabri (u. a.)

ISBN 10: 1447110900 / ISBN 13: 9781447110903

Published by Springer, 2012

About this Item

Functional Adaptive Control | An Intelligent Systems Approach | Simon G. Fabri (u. a.) | Taschenbuch | Communications and Control Engineering | xxi | Englisch | 2012 | Springer | EAN 9781447110903 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 106119048

Bibliographic Details

• Title: Functional Adaptive Control | An Intelligent Systems Approach
• Publisher: Springer
• Publication Date: 2012
• Language: English
• ISBN 10: 1447110900
• ISBN 13: 9781447110903
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 16D millimeters 235 millimeters width by 155 millimeters height by 16 millimeters depth
• Weight: 446 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

The field of intelligent control has recently emerged as a response to the challenge of controlling highly complex and uncertain nonlinear systems. It attempts to endow the controller with the key properties of adaptation, learn­ ing and autonomy. The field is still immature and there exists a wide scope for the development of new methods that enhance the key properties of in­ telligent systems and improve the performance in the face of increasingly complex or uncertain conditions. The work reported in this book represents a step in this direction. A num­ ber of original neural network-based adaptive control designs are introduced for dealing with plants characterized by unknown functions, nonlinearity, multimodal behaviour, randomness and disturbances. The proposed schemes achieve high levels of performance by enhancing the controller's capability for adaptation, stabilization, management of uncertainty, and learning. Both deterministic and stochastic plants are considered. In the deterministic case, implementation, stability and convergence is­ sues are addressed from the perspective of Lyapunov theory. When compared with other schemes, the methods presented lead to more efficient use of com­ putational storage and improved adaptation for continuous-time systems, and more global stability results with less prior knowledge in discrete-time sys­ tems.