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New Fuzzy Logic Study Findings Reported from Concordia University (Fuzzy gain-scheduled active fault-tolerant control of a wind turbine)

August 8, 2014

By a News Reporter-Staff News Editor at Energy Weekly News -- A new study on Fuzzy Logic is now available. According to news reporting from Montreal, Canada, by VerticalNews journalists, research stated, "Advanced fault detection and accommodation schemes are required for ensuring efficient and reliable operation of modern wind turbines. This paper presents a novel approach in designing a fault detection and diagnosis (FDD) and fault-tolerant control (FTC) scheme for a wind turbine using fuzzy modeling, identification and control techniques."

The news correspondents obtained a quote from the research from Concordia University, "First, an improved gain-scheduled proportional-integral (PI) control system based on fuzzy gain scheduling (FGS) technique for multi-input and multi-output wind turbine system is designed. Then, to accommodate sensor faults and based on a signal correction algorithm, an active fault-tolerant control system (AFTCS) is developed as an extension of the gain-scheduled PI control system. The AFTCS exploits the fault information from a model-based FDD scheme developed using fuzzy modeling and identification method. The proposed schemes are evaluated by a series of simulations on a well-known large off-shore wind turbine benchmark in the presence of wind turbulences, measurement noises, and different realistic fault scenarios."

According to the news reporters, the research concluded: "All results indicate high effectiveness and robustness of the designed control systems in both fault-free and faulty operations of the wind turbine."

For more information on this research see: Fuzzy gain-scheduled active fault-tolerant control of a wind turbine. Journal of the Franklin Institute-Engineering and Applied Mathematics, 2014;351(7):3677-3706. Journal of the Franklin Institute-Engineering and Applied Mathematics can be contacted at: Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England.

Our news journalists report that additional information may be obtained by contacting H. Badihi, Concordia University, Dept. of Mech & Ind Engn, Montreal, PQ H3G 1M8, Canada. Additional authors for this research include Y.M. Zhang and H. Hong.

Keywords for this news article include: Quebec, Canada, Montreal, Oil & Gas, Fuzzy Logic, Wind Energy, North and Central America

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Source: Energy Weekly News

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