{"title":"Disturbance rejection controller design based on nonlinear with fuzzy approximation technique for a tidal turbine system","authors":"Mustafa Wassef Hasan","doi":"10.1016/j.jksues.2023.09.003","DOIUrl":null,"url":null,"abstract":"In this work, a novel disturbance rejection controller based on a nonlinear fractional order proportional integral derivative with fuzzy (NLFOPIDF) approximation and an adaptive law technique for a 160 kW two horizontal axis parts tidal turbine model is proposed. The tidal turbine system encounters gigantic unknown uncertainties with external and internal disturbances induced by fatigue forces and non-uniform operative thrust and turbulence deviations caused by the effect of wind and wave movements. The main working purpose of the tidal turbine system is to extract the maximum power generated by obtaining and tracking the optimal turbine speed. To track the optimal speed turbine, two controller loops are synthesized for the tidal turbine dynamics (outer loop) and current dynamics in the q-axis component (inner loop). The stability and convergence are verified for the outer and inner loops using a candidate Lyapunov function. An approximation fuzzy function is proposed to estimate the nonlinear dynamics of the tidal turbine system, and an adaptive technique is applied to adapt the tidal turbine system against the variation in nonlinear dynamics. The results demonstrate that the NLFOPIDF controller is superior to other works in optimal power generation and optimal turbine speed tracking. Moreover, this controller can be used to achieve the maximum power coefficients to get the optimal power generation.","PeriodicalId":35558,"journal":{"name":"Journal of King Saud University, Engineering Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of King Saud University, Engineering Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.jksues.2023.09.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Chemical Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
In this work, a novel disturbance rejection controller based on a nonlinear fractional order proportional integral derivative with fuzzy (NLFOPIDF) approximation and an adaptive law technique for a 160 kW two horizontal axis parts tidal turbine model is proposed. The tidal turbine system encounters gigantic unknown uncertainties with external and internal disturbances induced by fatigue forces and non-uniform operative thrust and turbulence deviations caused by the effect of wind and wave movements. The main working purpose of the tidal turbine system is to extract the maximum power generated by obtaining and tracking the optimal turbine speed. To track the optimal speed turbine, two controller loops are synthesized for the tidal turbine dynamics (outer loop) and current dynamics in the q-axis component (inner loop). The stability and convergence are verified for the outer and inner loops using a candidate Lyapunov function. An approximation fuzzy function is proposed to estimate the nonlinear dynamics of the tidal turbine system, and an adaptive technique is applied to adapt the tidal turbine system against the variation in nonlinear dynamics. The results demonstrate that the NLFOPIDF controller is superior to other works in optimal power generation and optimal turbine speed tracking. Moreover, this controller can be used to achieve the maximum power coefficients to get the optimal power generation.
期刊介绍:
Journal of King Saud University - Engineering Sciences (JKSUES) is a peer-reviewed journal published quarterly. It is hosted and published by Elsevier B.V. on behalf of King Saud University. JKSUES is devoted to a wide range of sub-fields in the Engineering Sciences and JKSUES welcome articles of interdisciplinary nature.