{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T16:00:24Z","timestamp":1777910424651,"version":"3.51.4"},"reference-count":26,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2018,5,23]],"date-time":"2018-05-23T00:00:00Z","timestamp":1527033600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Transactions of the Institute of Measurement and Control"],"published-print":{"date-parts":[[2019,2]]},"abstract":"<jats:p>Pitch angle control is considered as a practical technique for power regulation above the rated wind speed. As a conventional pitch control, commonly the proportional and integral (PI) controller is used. However, the PI-type may not have a suitable performance if the controlled system contains non-linearity, as the wind turbine system or the desired wind trajectory varies with higher frequency. In the presence of modeling uncertainties, the necessity of methods presenting controllers with appropriate performance as the advanced control strategies is inevitable. The control approach based on Particle Swarm Optimization (PSO) algorithm may have the potential when the system contains strong non-linearity, such as strong wind turbulence. In this work, a new pitch control method based on PSO is developed. The design of the proposed strategy and its comparisons with a fuzzy logic controller and a conventional PI controller are carried out. The simulation results demonstrate that our developed approach has regulated both the output aerodynamic power and the speed in the nominal range. Results indicate that the new proposed PSO technique outperforms one of the best and earliest methods in smoothing the output power during wind fluctuations.<\/jats:p>","DOI":"10.1177\/0142331218764594","type":"journal-article","created":{"date-parts":[[2018,5,23]],"date-time":"2018-05-23T09:03:49Z","timestamp":1527066229000},"page":"647-656","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":16,"title":["Smoothing wind power fluctuations by particle swarm optimization-based pitch angle controller"],"prefix":"10.1177","volume":"41","author":[{"given":"Mouna","family":"Ben Smida","sequence":"first","affiliation":[{"name":"The National Engineering School of Monastir (ENIM), University of Monastir, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anis","family":"Sakly","sequence":"additional","affiliation":[{"name":"The National Engineering School of Monastir (ENIM), University of Monastir, 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