Abstract
AbstractIn this paper, we aim to study nonlinear time-periodic systems using the Koopman operator, which provides a way to approximate the dynamics of a nonlinear system by a linear time-invariant system of higher order. We propose for the considered system class a specific choice of Koopman basis functions combining the Taylor and Fourier bases. This basis allows to recover all equations necessary to perform the harmonic balance method as well as the Hill analysis directly from the linear lifted dynamics. The key idea of this paper is using this lifted dynamics to formulate a new method to obtain stability information from the Hill matrix. The error-prone and computationally intense task known by sorting, which means identifying the best subset of approximate Floquet exponents from all available candidates, is circumvented in the proposed method. The Mathieu equation and an n-DOF generalization are used to exemplify these findings.
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Applied Mathematics,Mechanical Engineering,Ocean Engineering,Aerospace Engineering,Control and Systems Engineering
Reference60 articles.
1. Mauroy, A., Mezić, I., Susuki, Y. (eds.): The Koopman Operator in Systems and Control: Concepts, Methodologies and Applications. Lecture Notes in Control and Information Sciences, vol. 484. Springer, Cham (2020)
2. Brunton, S.L., Budišić, M., Kaiser, E., Kutz, J.N.: Modern Koopman theory for dynamical systems. SIAM Rev. 64(2), 229–340 (2022). https://doi.org/10.1137/21m1401243
3. Williams, M.O., Kevrekidis, I.G., Rowley, C.W.: A data-driven approximation of the Koopman operator: extending dynamic mode decomposition. J. Nonlinear Sci. 25(6), 1307–1346 (2015). https://doi.org/10.1007/s00332-015-9258-5
4. Kono, Y., Susuki, Y., Hikihara, T.: Modeling of advective heat transfer in a practical building atrium via Koopman mode decomposition. In: Mauroy, A., Mezić, I., Susuki, Y. (eds.) The Koopman Operator in Systems and Control: Concepts, Methodologies, and Applications, pp. 481–506. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-35713-9_18
5. Korda, M., Mezić, I.: Koopman model predictive control of nonlinear dynamical systems. In: Mauroy, A., Mezić, I., Susuki, Y. (eds.) The Koopman Operator in Systems and Control: Concepts, Methodologies and Applications, pp. 235–255. Springer, Cham (2020)
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献