An Introduction to intelligent and autonomous control
著者
書誌事項
An Introduction to intelligent and autonomous control
Kluwer Academic, c1993
大学図書館所蔵 全24件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
The area of intelligent control is a fusion of a number of research areas in engineering computer science and mathematics, which has evolved from conventional control to enhance the existing nonlinear, optimal, adaptive and stochastic control methods. Intelligent control techniques are currently being utilized for closed-loop feedback control in space-based applications, manufacturing systems, robotic systems, avionic systems, among others, to improve system performance, reliability and efficiency. Overall, the primary objective of intelligent control is to enhance the performance of the system to the extent that it achieves some level of autonomous control. This work provides an introduction to, and survey of, the vital and emerging area of intelligent control by leading researchers in the area. Contributors to "An Introduction to Intelligent and Autonomous Control" are world-wide experts who have been invited on the strength of their research. The fundamental theory, archictectures and perspectives on intelligent control are presented.
Approaches to intelligent control, including expert control, planning systems, fuzzy control, neural control and learning control are studied in detail. Applications are introduced via robotic systems, avionic systems and failure diagnosis for process operations. "An Introduction to Intelligent and Autonomous Control" is designed as a reference for professionals and academic researchers and may also be used as the foundation for graduate level courses on intelligent and autonomous control.
目次
- Part 1 Theory and architectures: introduction to intelligent control systems with high degrees of autonomy, P.A. Antsaklis and K.M. Passino
- a reference model architecture for intelligent systems design, J.S. Albus
- model-based architecture concepts for autonomous systems design and simulation, B.P. Zeigler and Sungdo Chi
- design of structure-based hierarchies for distributed intelligent control, L. Acar and U. Ozguner
- modelling and design of distributed intelligence systems, A.H. Levis
- nested hierarchical control, A. Meystel. Part 2 Design approaches and techniques: expert control, K.J. Astrom and K.-E. Arzen
- modelling and analysis of artificially intelligent planning systems, K.M. Passino and P.J. Antsaklis
- fuzzy and neural control, H.R. Berenji
- learning control systems, J.A. Farrell and W. Baker
- learning control methods, needs and architectures, M.M. Kokar
- learning in control, E. Grant. Part 3 Applications: intellingent robot prehension, Thang N. Nguyen and H. Stephanou
- modelling of multi-sensory robotic systems with failure diagnostic capabilities, K.P. Valavanis and G. Seetharaman
- AUTOCREW - a paradigm for intelligent flight control, B.L. Belkin and R.F. Stengel
- a framework for knowledge-based diagnosis in process operations, P.R. Prased and J.F. Davis.
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