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Hereafter, the new control law is designed using the previously estimated fault information. The actuator efficiency estimator uses as design parameters, respectively, the performance index <jats:italic>\u03b3<\/jats:italic> against the wind and the learning rate \u039e. of the fault estimation algorithm. The study shows that the choice of the previous two parameters impacts the response time of the fault estimation and the correlation of the tracking error with the wind. The aim is to choose a small fault estimation response time while keeping a weak correlation between the tracking error and the wind turbulence noise. Finally, a tuning strategy is elaborated to choose the suitable <jats:italic>\u03b3<\/jats:italic> and <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"M1\"><mml:mi>\u039e<\/mml:mi><\/mml:math> to match the reconfiguration objective.<\/jats:p>","DOI":"10.1155\/2020\/6210407","type":"journal-article","created":{"date-parts":[[2020,2,12]],"date-time":"2020-02-12T18:34:11Z","timestamp":1581532451000},"page":"1-17","source":"Crossref","is-referenced-by-count":8,"title":["Optimal Fault Tolerant Control of Large-Scale Wind Turbines in the Case of the Pitch Actuator Partial Faults"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0105-898X","authenticated-orcid":true,"given":"Younes Ait","family":"El Maati","sequence":"first","affiliation":[{"name":"Cadi Ayad University, Laboratory of Electrical Engineering and Control Systems (LGECOS), National School of Applied Sciences, Av. 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