Namura Norihisa, Takata Shohei, Yamaguchi Katsunori, Kobayashi Ryota, Nakao Hiroya
Department of Systems and Control Engineering, Tokyo Institute of Technology, Tokyo 152-8552, Japan.
Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8561, Japan; Mathematics and Informatics Center, The University of Tokyo, Tokyo 113-8656, Japan; and JST, PRESTO, Saitama 332-0012, Japan.
Phys Rev E. 2022 Jul;106(1-1):014204. doi: 10.1103/PhysRevE.106.014204.
We propose a method for estimating the asymptotic phase and amplitude functions of limit-cycle oscillators using observed time series data without prior knowledge of their dynamical equations. The estimation is performed by polynomial regression and can be solved as a convex optimization problem. The validity of the proposed method is numerically illustrated by using two-dimensional limit-cycle oscillators as examples. As an application, we demonstrate data-driven fast entrainment with amplitude suppression using the optimal periodic input derived from the estimated phase and amplitude functions.
