Bayesian system identification and chaotic prediction from data for stochastic Mathieu-van der Pol-Duffing energy harvester  

作　　者：Di Liu Shen Xu Jinzhong Ma 

机构地区：[1]School of Mathematics Sciences,Shanxi University,030006,Taiyuan,Shanxi,China

出　　处：《Theoretical & Applied Mechanics Letters》2023年第2期89-92,共4页力学快报（英文版）

基　　金：This work is supported by the National Nature Science Founda-tion of China(Nos.11972019 and 12102237).

摘　　要：In this paper,the approximate Bayesian computation combines the particle swarm optimization and se-quential Monte Carlo methods,which identify the parameters of the Mathieu-van der Pol-Duffing chaotic energy harvester system.Then the proposed method is applied to estimate the coefficients of the chaotic model and the response output paths of the identified coefficients compared with the observed,which verifies the effectiveness of the proposed method.Finally,a partial response sample of the regular and chaotic responses,determined by the maximum Lyapunov exponent,is applied to detect whether chaotic motion occurs in them by a 0-1 test.This paper can provide a reference for data-based parameter iden-tification and chaotic prediction of chaotic vibration energy harvester systems.

关 键 词：Vibration energy harvester Approximate Bayesian computation 0–1 test Parameter identification Chaotic prediction 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]