Modern Adaptive Fuzzy Control Systems [electronic resource] / by Ardashir Mohammadzadeh, Mohammad Hosein Sabzalian, Chunwei Zhang, Oscar Castillo, Rathinasamy Sakthivel, Fayez F. M. El-Sousy.

Por: Mohammadzadeh, Ardashir [author.]Colaborador(es): Sabzalian, Mohammad Hosein [author.] | Zhang, Chunwei [author.] | Castillo, Oscar [author.] | Sakthivel, Rathinasamy [author.] | El-Sousy, Fayez F. M [author.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Studies in Fuzziness and Soft Computing ; 421Editor: Cham : Springer International Publishing : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: X, 157 p. 95 illus., 91 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031173936Tema(s): Computational intelligence | Control engineering | Artificial intelligence | Computational Intelligence | Control and Systems Theory | Artificial IntelligenceFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTexto
Contenidos:
Chapter 1: An Introduction to Fuzzy and Fuzzy Control Systems -- Chapter 2: Classification of Adaptive Fuzzy Controllers -- Chapter 3: Type-2 Fuzzy Systems -- Chapter 4: Training Interval Type-2 Fuzzy Systems Based on Error Backpropagation.
En: Springer Nature eBookResumen: This book explains the basic concepts, theory and applications of fuzzy systems in control in a simple unified approach with clear ex-amples and simulations in the MATLAB programming language. Fuzzy systems, especially, type-2 neuro-fuzzy systems, are now used extensively in various engineering fields for different purposes. In plain language, this book aims to practically explain fuzzy sys-tems and different methods of training and optimizing these systems. For this purpose, type-2 neuro-fuzzy systems are first analyzed along with various methods of training and optimizing these systems through implementation in MATLAB. These systems are then em-ployed to design adaptive fuzzy controllers. The authors aim at pre-senting all the well-known optimization methods clearly and code them in the MATLAB language.
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Chapter 1: An Introduction to Fuzzy and Fuzzy Control Systems -- Chapter 2: Classification of Adaptive Fuzzy Controllers -- Chapter 3: Type-2 Fuzzy Systems -- Chapter 4: Training Interval Type-2 Fuzzy Systems Based on Error Backpropagation.

This book explains the basic concepts, theory and applications of fuzzy systems in control in a simple unified approach with clear ex-amples and simulations in the MATLAB programming language. Fuzzy systems, especially, type-2 neuro-fuzzy systems, are now used extensively in various engineering fields for different purposes. In plain language, this book aims to practically explain fuzzy sys-tems and different methods of training and optimizing these systems. For this purpose, type-2 neuro-fuzzy systems are first analyzed along with various methods of training and optimizing these systems through implementation in MATLAB. These systems are then em-ployed to design adaptive fuzzy controllers. The authors aim at pre-senting all the well-known optimization methods clearly and code them in the MATLAB language.

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