New Findings from Tianjin University of Science and Technology in Energy Provides New Insights (Fault-Tolerant Control of Doubly-Fed Wind Turbine Generation Systems under Sensor Fault Conditions)
- Nov 14, 2019 4:26 am GMT
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2019 NOV 13 (NewsRx) -- By a News Reporter-Staff News Editor at Energy Daily News -- Fresh data on Energy are presented in a new report. According to news reporting out of Tianjin, People’s Republic of China, by NewsRx editors, research stated, “This paper studies the fault-tolerant control problem of uncertain doubly-fed wind turbine generation systems with sensor faults. Considering the uncertainty of the system, a fault-tolerant control strategy based on a T-S fuzzy observer is proposed.”
Funders for this research include National Natural Science Foundation of China-Yunnan Joint Fund, Tianjin Science and Technology Support Foundation of China.
Our news journalists obtained a quote from the research from the Tianjin University of Science and Technology, “The fuzzy observer is established based on the T-S fuzzy model of the uncertain nonlinear system. According to the comparison and analysis of residual between the state estimation of the fuzzy observer output and the measured value of the real sensor, a fault detection and isolation (FDI) based on T-S fuzzy observer is designed. Then by using a Parallel Distributed Compensation (PDC) method we design the robust fuzzy controller. Finally, the necessary and sufficient conditions for the stability of the closed-loop system are proved by quoting Lyapunov stability theory.”
According to the news editors, the research concluded: “The simulation results verify the effectiveness of the proposed control method.”
For more information on this research see: Fault-Tolerant Control of Doubly-Fed Wind Turbine Generation Systems under Sensor Fault Conditions. Energies, 2019;12(17):3239. Energies can be contacted at: Mdpi, St Alban-Anlage 66, Ch-4052 Basel, Switzerland.
Our news journalists report that additional information may be obtained by contacting G.D. You, Tianjin University of Science and Technology, College of Electronic Information and Automation, Tianjin 300222, People’s Republic of China. Additional authors for this research include T. Xu, H.L. Su, X.X. Hou, X. Wang, C.X. Fang and J.S. Li.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.3390/en12173239. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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