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Intelligent Control Design and MATLAB Simulation [electronic resource] / by Jinkun Liu.

By: Liu, Jinkun [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XV, 290 p. 137 illus., 95 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789811052637.Subject(s): Control engineering | Robotics | Automation | Computer simulation | Industrial engineering | Production engineering | Engineering design | Control, Robotics, Automation | Computer Modelling | Industrial and Production Engineering | Engineering DesignAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 629.8 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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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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.

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