{"title":"Improved pole-placement for adaptive pitch control","authors":"S. Sahu, S. Behera","doi":"10.1504/ijsi.2019.10025728","DOIUrl":null,"url":null,"abstract":"This paper presents an improved technique to regulate the pitch angle of a wind turbine benchmark model (WTBM) implemented in MATLAB SIMULINK environment. As the model is nonlinear in nature, to accomplish the desired power production level in the constant power region, an adaptive controller is implemented. It takes care of the pitch control with online estimates of the plant parameters that are susceptible to change due to disturbances. Here, the controller design is based on the pole-placement methodology for a self-tuning controller (STC). Location of the desired pair of poles is defined by the damping factor and natural frequency. The selection of these parameters is performed by utilising particle swarm optimisation (PSO), constriction factor-based PSO (CFBPSO), genetic algorithm (GA), modified grey wolf optimisation (MGWO) and improved sine cosine algorithm (ISCA) and the results are put side by side for a consistent set of algorithm parameters. A Monte Carlo simulation has been carried out for comparison of the algorithms. The achieved results show the improvement in performance by employing ISCA for pole-placement of an adaptive STC controller.","PeriodicalId":44265,"journal":{"name":"International Journal of Swarm Intelligence Research","volume":"24 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Swarm Intelligence Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijsi.2019.10025728","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents an improved technique to regulate the pitch angle of a wind turbine benchmark model (WTBM) implemented in MATLAB SIMULINK environment. As the model is nonlinear in nature, to accomplish the desired power production level in the constant power region, an adaptive controller is implemented. It takes care of the pitch control with online estimates of the plant parameters that are susceptible to change due to disturbances. Here, the controller design is based on the pole-placement methodology for a self-tuning controller (STC). Location of the desired pair of poles is defined by the damping factor and natural frequency. The selection of these parameters is performed by utilising particle swarm optimisation (PSO), constriction factor-based PSO (CFBPSO), genetic algorithm (GA), modified grey wolf optimisation (MGWO) and improved sine cosine algorithm (ISCA) and the results are put side by side for a consistent set of algorithm parameters. A Monte Carlo simulation has been carried out for comparison of the algorithms. The achieved results show the improvement in performance by employing ISCA for pole-placement of an adaptive STC controller.
期刊介绍:
The mission of the International Journal of Swarm Intelligence Research (IJSIR) is to become a leading international and well-referred journal in swarm intelligence, nature-inspired optimization algorithms, and their applications. This journal publishes original and previously unpublished articles including research papers, survey papers, and application papers, to serve as a platform for facilitating and enhancing the information shared among researchers in swarm intelligence research areas ranging from algorithm developments to real-world applications.