Adaptive parameter identification of Bouc–Wen hysteresis model for a vibration system using magnetorheological elastomer

2021 ◽  
pp. 106848
Author(s):  
Xuan Bao Nguyen ◽  
Toshihiko Komatsuzaki ◽  
Hoa Thi Truong
Keyword(s):  
Parameter Identification ◽  
Vibration System ◽  
Hysteresis Model ◽  
Magnetorheological Elastomer ◽  
Adaptive Parameter

scholarly journals Fault Prognosis for Power Electronics Systems Using Adaptive Parameter Identification

2017 ◽  
Vol 53 (3) ◽  
pp. 2862-2870 ◽  
Author(s):  
Jason Poon ◽  
Palak Jain ◽  
Costas Spanos ◽  
Sanjib Kumar Panda ◽  
Seth R. Sanders
Keyword(s):  
Parameter Identification ◽  
Power Electronics ◽  
Adaptive Parameter ◽  
Fault Prognosis

An improved lion swarm optimization for parameters identification of photovoltaic cell models

2019 ◽  
Vol 42 (6) ◽  
pp. 1191-1203
Author(s):  
Zhong-qiang Wu ◽  
Zong-kui Xie ◽  
Chong-yang Liu
Keyword(s):  
Parameter Identification ◽  
Cell Model ◽  
Chaotic Map ◽  
Photovoltaic Cell ◽  
Standard Test ◽  
Local Optimum ◽  
Intelligent Algorithm ◽  
Swarm Optimization ◽  
Test Function ◽  
Adaptive Parameter

In this paper, a parameter identification method of photovoltaic cell model based on improved lion swarm optimization is presented. Lion swarm optimization is a novel intelligent algorithm proposed in recent years, but it has problems such as local optimum and slow convergence. To overcome such limitations, we can combine the tent chaotic map, adaptive parameter and chaotic search strategy to further improve the search ability of the algorithm and avoid trapping in local optimum. The simulation of standard test function shows that the performance of improved lion swarm algorithm is superior to the other six algorithms. Then the algorithm is applied to the parameter identification of photovoltaic cells under two kinds of models and different irradiance, the simulation results verify the superiority and effectiveness of the improved lion swarm optimization in the application of photovoltaic cell parameter identification.

scholarly journals Parameter Identification of Weakly Nonlinear Vibration System in Frequency Domain

2004 ◽  
Vol 11 (5-6) ◽  
pp. 685-692 ◽  
Author(s):  
Jiehua Peng ◽  
Jiashi Tang ◽  
Zili Chen
Keyword(s):  
Parameter Identification ◽  
Frequency Response ◽  
Nonlinear Vibration ◽  
Frequency Domain ◽  
Response Function ◽  
Frequency Response Function ◽  
Physical Parameters ◽  
Vibration System ◽  
Weakly Nonlinear ◽  
Nonlinear Vibration System

A new method of identifying parameters of nonlinearly vibrating system in frequency domain is presented in this paper. The problems of parameter identification of the nonlinear dynamic system with nonlinear elastic force or nonlinear damping force are discussed. In the method, the mathematic model of parameter identification is frequency response function. Firstly, by means of perturbation method the frequency response function of weakly nonlinear vibration system is derived. Next, a parameter transformation is made and the frequency response function becomes a linear function of the new parameters. Then, based on this function and with the least square method, physical parameters of the system are identified. Finally, the applicability of the proposed technique is confirmed by numerical simulation.

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