Robust and fault-tolerant control [electronic resource] : neural-network-based solutions / by Krzysztof Patan.
- 作者： Patan, Krzysztof.
- 其他作者：
- 其他題名：
- Studies in systems, decision and control ;
- 出版： Cham : Springer International Publishing :Imprint: Springer 2019.
- 叢書名： Studies in systems, decision and control,v.197
- 主題： Fault tolerance (Engineering) , Control theory. , Fault location (Engineering) , Neural networks (Computer science) , Control and Systems Theory. , Artificial Intelligence. , Industrial Chemistry/Chemical Engineering. , Automotive Engineering. , Aerospace Technology and Astronautics.
- ISBN： 9783030118693 (electronic bk.) 、 9783030118686 (paper)
- URL：
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電子書(校內)
- 一般註：Introduction -- Neural Networks -- Robust and Fault-Tolerant Control -- Model Predictive Control -- Control Reconfiguration -- Iterative Learning Control -- Concluding Remarks and Further Research Directions. E1084學校採購電子書
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讀者標籤：
- 系統號： 000274426 | 機讀編目格式
館藏資訊
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.
摘要註
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.