{"title":"Multiple time-varying formation tracking of multiple heterogeneous Euler–Lagrange systems via prescribed-time hierarchical control algorithms in task space","authors":"Lin-Jing Chen, B. Xiao, Tao Han, Huaicheng Yan","doi":"10.1007/s11071-023-09212-0","DOIUrl":"https://doi.org/10.1007/s11071-023-09212-0","url":null,"abstract":"","PeriodicalId":19723,"journal":{"name":"Nonlinear Dynamics","volume":"32 12","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139441529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Learn from one and predict all: single trajectory learning for time delay systems","authors":"X. Ji, Gábor Orosz","doi":"10.1007/s11071-023-09206-y","DOIUrl":"https://doi.org/10.1007/s11071-023-09206-y","url":null,"abstract":"","PeriodicalId":19723,"journal":{"name":"Nonlinear Dynamics","volume":"2 2","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139444340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Camille Saint-Martin, A. Morel, L. Charleux, Émile Roux, D. Gibus, A. Benhemou, A. Badel
{"title":"Optimized and robust orbit jump for nonlinear vibration energy harvesters","authors":"Camille Saint-Martin, A. Morel, L. Charleux, Émile Roux, D. Gibus, A. Benhemou, A. Badel","doi":"10.1007/s11071-023-09188-x","DOIUrl":"https://doi.org/10.1007/s11071-023-09188-x","url":null,"abstract":"","PeriodicalId":19723,"journal":{"name":"Nonlinear Dynamics","volume":"31 7","pages":""},"PeriodicalIF":5.6,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139445817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nonlinear DynamicsPub Date : 2024-01-01Epub Date: 2024-08-05DOI: 10.1007/s11071-024-10050-x
Soumyajit Seth, Abhijit Bera, Vikram Pakrashi
{"title":"Exploring chaos and ergodic behavior of an inductorless circuit driven by stochastic parameters.","authors":"Soumyajit Seth, Abhijit Bera, Vikram Pakrashi","doi":"10.1007/s11071-024-10050-x","DOIUrl":"10.1007/s11071-024-10050-x","url":null,"abstract":"<p><p>There exist extensive studies on periodic and random perturbations of various smooth maps investigating their dynamics. Unlike smooth maps, non-smooth maps are yet to be studied extensively under a stochastic regime. This paper presents a stochastic piecewise-smooth map derived from a simple inductorless switching circuit. The stochasticity is introduced in parameter values. The distribution of the parameter values is bounded and randomly selected from uniform and triangular distributions and ranges between high and low bifurcation parameter values of the deterministic map. Due to this inherent stochasticity in parameter values, the time evolution of the state variable cannot be predicted at a specific time instant. We observe that the state variable exhibits completely ergodic behavior when the minimum value of the parameter is the same as the minimum bifurcation parameter of the deterministic system. However, the ensemble average of the state variable converges to a fixed value. The system demonstrates nonchaotic behavior for a particular range of parameter values but the deterministic map in that bifurcation range shows interplay between chaos and periodic orbits. The values of Lyapunov exponents decrease monotonically with increased asymmetry of the distribution from which the bifurcation parameter values are chosen. We determine the probability density function of the stochastic map and verify its invariance under initial conditions. The most noteworthy result is the disappearance of chaotic behavior when the lower range of the distribution is varied while maintaining a fixed upper threshold for a particular distribution, even though the deterministic map exhibits an array of periodic and chaotic behaviors within the range. As the period-incrementing cascade with chaotic inclusion only occurs in nonsmooth maps, this paper numerically shows the stochasticity of a piecewise-smooth map obtained from a practical system for the first time where randomness is introduced in the parameter space.</p>","PeriodicalId":19723,"journal":{"name":"Nonlinear Dynamics","volume":"112 21","pages":"19441-19462"},"PeriodicalIF":5.2,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362311/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142110571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nonlinear DynamicsPub Date : 2024-01-01Epub Date: 2024-08-15DOI: 10.1007/s11071-024-10026-x
George Haller, Bálint Kaszás
{"title":"Data-driven linearization of dynamical systems.","authors":"George Haller, Bálint Kaszás","doi":"10.1007/s11071-024-10026-x","DOIUrl":"10.1007/s11071-024-10026-x","url":null,"abstract":"<p><p>Dynamic mode decomposition (DMD) and its variants, such as extended DMD (EDMD), are broadly used to fit simple linear models to dynamical systems known from observable data. As DMD methods work well in several situations but perform poorly in others, a clarification of the assumptions under which DMD is applicable is desirable. Upon closer inspection, existing interpretations of DMD methods based on the Koopman operator are not quite satisfactory: they justify DMD under assumptions that hold only with probability zero for generic observables. Here, we give a justification for DMD as a local, leading-order reduced model for the dominant system dynamics under conditions that hold with probability one for generic observables and non-degenerate observational data. We achieve this for autonomous and for periodically forced systems of finite or infinite dimensions by constructing linearizing transformations for their dominant dynamics within attracting slow spectral submanifolds (SSMs). Our arguments also lead to a new algorithm, data-driven linearization (DDL), which is a higher-order, systematic linearization of the observable dynamics within slow SSMs. We show by examples how DDL outperforms DMD and EDMD on numerical and experimental data.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11071-024-10026-x.</p>","PeriodicalId":19723,"journal":{"name":"Nonlinear Dynamics","volume":"112 21","pages":"18639-18663"},"PeriodicalIF":5.2,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11362512/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142110570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}