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Springer Wind Turbine Control and Monitoring (Advances in Industrial Control)

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Description

Product Description Maximizing reader insights into the latest technical developments and trends involving wind turbine control and monitoring, fault diagnosis, and wind power systems, ‘Wind Turbine Control and Monitoring’ presents an accessible and straightforward introduction to wind turbines, but also includes an in-depth analysis incorporating illustrations, tables and examples on how to use wind turbine modeling and simulation software. Featuring analysis from leading experts and researchers in the field, the book provides new understanding, methodologies and algorithms of control and monitoring, computer tools for modeling and simulation, and advances the current state-of-the-art on wind turbine monitoring and fault diagnosis; power converter systems; and cooperative & fault-tolerant control systems for maximizing the wind power generation and reducing the maintenance cost. This book is primarily intended for researchers in the field of wind turbines, control, mechatronics and energy; postgraduates in the field of mechanical and electrical engineering; and graduate and senior undergraduate students in engineering wishing to expand their knowledge of wind energy systems. The book will also interest practicing engineers dealing with wind technology who will benefit from the comprehensive coverage of the theoretic control topics, the simplicity of the models and the use of commonly available control algorithms and monitoring techniques. From the Back Cover Maximizing reader insights into the latest technical developments and trends involving wind turbine control and monitoring, fault diagnosis, and wind power systems, ‘Wind Turbine Control and Monitoring’ presents an accessible and straightforward introduction to wind turbines, but also includes an in-depth analysis incorporating illustrations, tables and examples on how to use wind turbine modeling and simulation software. Featuring analysis from leading experts and researchers in the field, the book provides new understanding, methodologies and algorithms of control and monitoring, computer tools for modeling and simulation, and advances the current state-of-the-art on wind turbine monitoring and fault diagnosis; power converter systems; and cooperative & fault-tolerant control systems for maximizing the wind power generation and reducing the maintenance cost. This book is primarily intended for researchers in the field of wind turbines, control, mechatronics and energy; postgraduates in the field of mechanical and electrical engineering; and graduate and senior undergraduate students in engineering wishing to expand their knowledge of wind energy systems. The book will also interest practicing engineers dealing with wind technology who will benefit from the comprehensive coverage of the theoretic control topics, the simplicity of the models and the use of commonly available control algorithms and monitoring techniques. About the Author Ningsu Luo is Professor of Control Systems Engineering at Department of Electrical Engineering, Electronics and Automatic Control, University of Girona, Spain. He obtained his PhD in Control Engineering from Southeast University in 1990 and PhD in Physics Science from University of the Basque Country in 1994, respectively. His current research activities are focused on modeling, identification and control design for systems with complex dynamics, with application to control and monitoring of offshore floating wind turbines, mobile robotics, sustainable tillage, mechatronic systems, biomedical processes, active and semi-active control techniques for vibration mitigation in civil engineering structures and automotive suspension systems. Yolanda Vidal was born in Baleares, Spain, in 1977. She received the B.E. degree in mathematics in 1999 and the Ph.D. degree in Applied Mathematics in 2005 from the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain. Since 2002 she has been with the Department of Appl

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
23 August 2016
Listed Since
21 July 2016

Barcode

No barcode data available

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