{"title":"Tiltrotor whirl-flutter stability analysis using the maximum Lyapunov characteristic exponent estimated from time series","authors":"G. Cassoni","doi":"10.21741/9781644902813-7","DOIUrl":null,"url":null,"abstract":"Abstract. Stability analysis and assessment are fundamental in the analysis and design of dynamical systems. Particularly in rotorcraft dynamics, problems often exhibit time-periodic behavior, and modern designs consider nonlinearities to achieve a more accurate representation of the system dynamics. Nonlinearities in rotorcraft may arise from factors such as nonlinear damper constitutive laws or the influence of fluid-structure interaction, among others. Regardless of their origin, quantifying the stability of nonlinear systems typically relies on calculating their Jacobian matrix. However, accessing the Jacobian matrix of a system is often challenging or impractical, calling for the use of data-driven methods. This introduces additional complexity in capturing the characteristic dynamics of the system. Hence, a data-driven approach is proposed that utilizes the Largest Lyapunov Characteristic Exponent, obtained by analyzing the system's time series.","PeriodicalId":87445,"journal":{"name":"Materials Research Society symposia proceedings. Materials Research Society","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Research Society symposia proceedings. Materials Research Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21741/9781644902813-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract. Stability analysis and assessment are fundamental in the analysis and design of dynamical systems. Particularly in rotorcraft dynamics, problems often exhibit time-periodic behavior, and modern designs consider nonlinearities to achieve a more accurate representation of the system dynamics. Nonlinearities in rotorcraft may arise from factors such as nonlinear damper constitutive laws or the influence of fluid-structure interaction, among others. Regardless of their origin, quantifying the stability of nonlinear systems typically relies on calculating their Jacobian matrix. However, accessing the Jacobian matrix of a system is often challenging or impractical, calling for the use of data-driven methods. This introduces additional complexity in capturing the characteristic dynamics of the system. Hence, a data-driven approach is proposed that utilizes the Largest Lyapunov Characteristic Exponent, obtained by analyzing the system's time series.