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Intelligent control design and MATLA...

Liu, Jinkun.

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Intelligent control design and MATLAB simulation

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent control design and MATLAB simulation/ by Jinkun Liu.
作者:	Liu, Jinkun.
出版者:	Singapore :Springer Singapore : : 2018.,
面頁冊數:	xv, 290 p. :ill., digital ;24 cm.
內容註:	Introduction -- Expert control -- Mathmatic foundation of fuzzy control -- Fuzzy logic control -- Adaptive fuzzy control -- Neural Network -- Typical Neural Network -- Senior Neural Network -- Neural network control with gradient descend -- Adaptive neural network control -- Digital RBF Neural Network Control -- Intelligent optimization algorithms -- Iterative learning control.
Contained By:	Springer eBooks
標題:	Intelligent control systems. -
電子資源:	http://dx.doi.org/10.1007/978-981-10-5263-7
ISBN:	9789811052637

Intelligent control design and MATLAB simulation
Liu, Jinkun.

Intelligent control design and MATLAB simulation[electronic resource] /by Jinkun Liu. - Singapore :Springer Singapore :2018. - xv, 290 p. :ill., digital ;24 cm.

Introduction -- Expert control -- Mathmatic foundation of fuzzy control -- Fuzzy logic control -- Adaptive fuzzy control -- Neural Network -- Typical Neural Network -- Senior Neural Network -- Neural network control with gradient descend -- Adaptive neural network control -- Digital RBF Neural Network Control -- Intelligent optimization algorithms -- Iterative learning control.

This book offers a comprehensive introduction to intelligent control system design, using MATLAB simulation to verify typical intelligent controller designs. It also uses real-world case studies that present the results of intelligent controller implementations to illustrate the successful application of the theory. Addressing the need for systematic design approaches to intelligent control system design using neural network and fuzzy-based techniques, the book introduces the concrete design method and MATLAB simulation of intelligent control strategies; offers a catalog of implementable intelligent control design methods for engineering applications; provides advanced intelligent controller design methods and their stability analysis methods; and presents a sample simulation and Matlab program for each intelligent control algorithm. The main topics addressed are expert control, fuzzy logic control, adaptive fuzzy control, neural network control, adaptive neural contro l and intelligent optimization algorithms, providing several engineering application examples for each method.

ISBN: 9789811052637

Standard No.: 10.1007/978-981-10-5263-7doiSubjects--Uniform Titles:

MATLAB.
Subjects--Topical Terms:

546464
Intelligent control systems.

LC Class. No.: TJ217.5 / .L585 2017

Dewey Class. No.: 629.8

Intelligent control design and MATLAB simulation
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505 0 $a Introduction -- Expert control -- Mathmatic foundation of fuzzy control -- Fuzzy logic control -- Adaptive fuzzy control -- Neural Network -- Typical Neural Network -- Senior Neural Network -- Neural network control with gradient descend -- Adaptive neural network control -- Digital RBF Neural Network Control -- Intelligent optimization algorithms -- Iterative learning control.
520 $a This book offers a comprehensive introduction to intelligent control system design, using MATLAB simulation to verify typical intelligent controller designs. It also uses real-world case studies that present the results of intelligent controller implementations to illustrate the successful application of the theory. Addressing the need for systematic design approaches to intelligent control system design using neural network and fuzzy-based techniques, the book introduces the concrete design method and MATLAB simulation of intelligent control strategies; offers a catalog of implementable intelligent control design methods for engineering applications; provides advanced intelligent controller design methods and their stability analysis methods; and presents a sample simulation and Matlab program for each intelligent control algorithm. The main topics addressed are expert control, fuzzy logic control, adaptive fuzzy control, neural network control, adaptive neural contro l and intelligent optimization algorithms, providing several engineering application examples for each method.
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