2018/04/23 by Saeideh Khatiry Goharoodi, Kevin Dekemele, Goharoodi, Saeideh Khatiry +7
Engineering · #Chaotic Dynamics (nlin.CD) #Classical Physics (physics.class-ph) #Control Systems and Identification #FOS: Physical sciences #Iterative Learning Control Systems #Structural Health Monitoring Techniques
paper · pdf · doi:10.48550/arxiv.1805.03499
openalex publication_date 2018/04/23 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
In this paper we aim to apply an adaptation of the recently developed\ntechnique of sparse identification of nonlinear dynamical systems on a Duffing\nexperimental setup with cubic feedback of the output. The Duffing oscillator\ndescribed by nonlinear differential equation which demonstrates chaotic\nbehavior and bifurcations, has received considerable attention in recent years\nas it arises in many real-world engineering applications. Therefore its\nidentification is of interest for numerous practical problems. To adopt the\nexisting identification method to this application, the optimization process\nwhich identifies the most important terms of the model has been modified. In\naddition, the impact of changing the amount of regularization parameter on the\nmean square error of the fit has been studied. Selection of the true model is\ndone via balancing complexity and accuracy using Pareto front analysis. This\nstudy provides considerable insight into the employment of sparse\nidentification method on the real-world setups and the results show that the\ndeveloped algorithm is capable of finding the true nonlinear model of the\nconsidered application including a nonlinear friction term.\n