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Doubly Fed Induction Generators Control For Wind Energy Ruizcruz

  • SKU: BELL-5672810
Doubly Fed Induction Generators Control For Wind Energy Ruizcruz
$ 31.00 $ 45.00 (-31%)

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Doubly Fed Induction Generators Control For Wind Energy Ruizcruz instant download after payment.

Publisher: CRC Press
File Extension: EPUB
File size: 5.03 MB
Author: Ruiz-Cruz, Riemann; Sanchez, Edgar N
ISBN: 9781315332697, 9781315351735, 9781315368771, 9781498745840, 1315332698, 1315351730, 1315368773, 1498745849
Language: English
Year: 2016

Product desciption

Doubly Fed Induction Generators Control For Wind Energy Ruizcruz by Ruiz-cruz, Riemann; Sanchez, Edgar N 9781315332697, 9781315351735, 9781315368771, 9781498745840, 1315332698, 1315351730, 1315368773, 1498745849 instant download after payment.

Doubly Fed Induction Generators: Control for Wind Energyprovides a detailed source of information on the modeling and design of controllers for the doubly fed induction generator (DFIG) used in wind energy applications. Focusing on the use of nonlinear control techniques, this book:Discusses the main features and advantages of the DFIGDescribes key theoretical fundamentals and the DFIG mathematical modelDevelops controllers using inverse optimal control, sliding modes, and neural networksDevises an improvement to add robustness in the presence of parametric variationsDetails the results of real-time implementationsAll controllers presented in the book are tested in a laboratory prototype. Comparisons between the controllers are made by analyzing statistical measures applied to the control objectives.
Abstract: Doubly Fed Induction Generators: Control for Wind Energyprovides a detailed source of information on the modeling and design of controllers for the doubly fed induction generator (DFIG) used in wind energy applications. Focusing on the use of nonlinear control techniques, this book:Discusses the main features and advantages of the DFIGDescribes key theoretical fundamentals and the DFIG mathematical modelDevelops controllers using inverse optimal control, sliding modes, and neural networksDevises an improvement to add robustness in the presence of parametric variationsDetails the results of real-time implementationsAll controllers presented in the book are tested in a laboratory prototype. Comparisons between the controllers are made by analyzing statistical measures applied to the control objectives

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