Robust and Fault-Tolerant Control

von Krzysztof Patan

Neural-Network-Based Solutions

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Beschreibung

Robust and Fault-Tolerant Control proposes novel automatic control strategies for nonlinear systems developed by means of artificial neural networks and pays special attention to robust and fault-tolerant approaches. The book discusses robustness and fault tolerance in the context of model predictive control, fault accommodation and reconfiguration, and iterative learning control strategies. Expanding on its theoretical deliberations the monograph includes many case studies demonstrating how the proposed approaches work in practice. The most important features of the book include:

a comprehensive review of neural network architectures with possible applications in system modelling and control;
a concise introduction to robust and fault-tolerant control;
step-by-step presentation of the control approaches proposed;
an abundance of case studies illustrating the important steps in designing robust and fault-tolerant control; and
a large number of figures and tables facilitating the performance analysis of the control approaches described.

The material presented in this book will be useful for researchers and engineers who wish to avoid spending excessive time in searching neural-network-based control solutions. It is written for electrical, computer science and automatic control engineers interested in control theory and their applications. This monograph will also interest postgraduate students engaged in self-study of nonlinear robust and fault-tolerant control.
Robust and Fault-Tolerant Control proposes novel automatic control strategies for nonlinear systems developed by means of artificial neural networks and pays special attention to robust and fault-tolerant approaches. The book discusses robustness and fault tolerance in the context of model predictive control, fault accommodation and reconfiguration, and iterative learning control strategies. Expanding on its theoretical deliberations the monograph includes many case studies demonstrating how the proposed approaches work in practice. The most important features of the book include:

a comprehensive review of neural network architectures with possible applications in system modelling and control;
a concise introduction to robust and fault-tolerant control;
step-by-step presentation of the control approaches proposed;
an abundance of case studies illustrating the important steps in designing robust and fault-tolerant control; and
a large number of figures and tables facilitating the performance analysis of the control approaches described.

The material presented in this book will be useful for researchers and engineers who wish to avoid spending excessive time in searching neural-network-based control solutions. It is written for electrical, computer science and automatic control engineers interested in control theory and their applications. This monograph will also interest postgraduate students engaged in self-study of nonlinear robust and fault-tolerant control.
Equips the reader to solve problems in a wide class of nonlinear systems Provides opportunities for practice and experience with examples of robust and fault-tolerant control Allows the reader easy access to the uses of artificial neural networks in nonlinear control synthesis with a concise review

Autor*in

Krzysztof Patan

Themen in »Robust and Fault-Tolerant Control«

Control System Synthesis Artificial Neural Networks Dynamic Modelling Fault-tolerant Control Systems Robust Control Uncertainty Modelling

Stimmen zu »Robust and Fault-Tolerant Control«

“This monograph presents some ideas, concepts and new results in the field of robust fault-tolerant control. … This monograph opens up new possibilities for many researchers in this field to approach the front line of research.” (Anatoly Martynyuk, zbMATH 1422.93002, 2019)

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Details

ISBN: 9783030118693

Verlag: Springer International Publishing

Erscheinung: 16.03.2019