DEVELOPING A METHOD FOR IDENTIFICATION OF INTEGRAL NONLINEAR MODELS OF VISCOELASTIC MEDIA BASED ON A NONLINEAR DAMPING FUNCTION

Представлены модель, алгоритм и программный расчет нелинейного отклика среды на заданное возмущение для двухслойного полупространства. Теоретический подход основан на использовании функции Грина. Проведен анализ зависимости спектров синтетических акселерограмм от параметра нелинейности и частоты входного сигнала. Предложенная модель в полной мере учитывает физическую нелинейность: во‑первых, нелинейную связь «напряжение-деформация», во‑вторых, нелинейное затухание среды в зависимости от уровня деформации. Программный продукт может использоваться при прогнозировании нелинейного отклика грунта на ожидаемое расчетное землетрясение The model, algorithm and numerical results of the nonlinear response of the medium is presented. The theoretical approach is based on the use of the Green’s function. Analysis of the dependence of the spectra of synthetic accelerograms of the nonlinearity parameter and frequency of the input signal is carried out. The model takes into account the physical nonlinearity: at first, non-linear relationship «stress-strain», secondly, nonlinear damping medium depending on the strain level. The software can be used for predicting the nonlinear response of the ground to the expected estimated earthquake.

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An Optimization-Based Framework for Nonlinear Model Selection and Identification

Vibration ◽

10.3390/vibration2040020 ◽

2019 ◽

Vol 2 (4) ◽

pp. 311-331 ◽

Cited By ~ 1

Author(s):

Javad Taghipour ◽

Hamed Haddad Khodaparast ◽

Michael I. Friswell ◽

Hassan Jalali

Keyword(s):

Nonlinear Model ◽

Electromagnetic Force ◽

Nonlinear Models ◽

Taylor Series Expansion ◽

Nonlinear Damping ◽

Linear Quadratic ◽

Nonlinear Force ◽

Linear Damping ◽

Vibration Tests ◽

Fifth Order

This paper proposes an optimization-based framework to determine the type of nonlinear model present and identify its parameters. The objective in this optimization problem is to identify the parameters of a nonlinear model by minimizing the differences between the experimental and analytical responses at the measured coordinates of the nonlinear structure. The application of the method is demonstrated on a clamped beam subjected to a nonlinear electromagnetic force. In the proposed method, the assumption is that the form of nonlinear force is not known. For this reason, one may assume that any nonlinear force can be described using a Taylor series expansion. In this paper, four different possible nonlinear forms are assumed to model the electromagnetic force. The parameters of these four nonlinear models are identified from experimental data obtained from a series of stepped-sine vibration tests with constant acceleration base excitation. It is found that a nonlinear model consisting of linear damping and linear, quadratic, cubic, and fifth order stiffness provides excellent agreement between the predicted responses and the corresponding measured responses. It is also shown that adding a quadratic nonlinear damping does not lead to a significant improvement in the results.

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Control of uncertain nonlinear systems using mixed nonlinear damping function and backstepping techniques

2012 IEEE International Conference on Control System, Computing and Engineering ◽

10.1109/iccsce.2012.6487124 ◽

2012 ◽

Cited By ~ 2

Author(s):

Muhammad Nizam Kamarudin ◽

Abdul Rashid Husain ◽

Mohamad Noh Ahmad

Keyword(s):

Nonlinear Systems ◽

Nonlinear Damping ◽

Uncertain Nonlinear Systems ◽

Damping Function

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UNCERTAIN CHAOTIC SYSTEM CONTROL VIA ADAPTIVE NEURAL DESIGN

International Journal of Bifurcation and Chaos ◽

10.1142/s0218127402004930 ◽

2002 ◽

Vol 12 (05) ◽

pp. 1097-1109 ◽

Cited By ~ 53

Author(s):

S. S. GE ◽

C. WANG

Keyword(s):

Neural Control ◽

Chaotic Systems ◽

Nonlinear Models ◽

Feedback System ◽

Nonlinear Damping ◽

System Control ◽

Feedback Form ◽

Uncertain Chaotic Systems ◽

Robust Control Design ◽

Strict Feedback

Though chaotic behaviors are exhibited in many simple nonlinear models, physical chaotic systems are much more complex and contain many types of uncertainties. This paper presents a robust adaptive neural control scheme for a class of uncertain chaotic systems in the disturbed strict-feedback form, with both unknown nonlinearities and uncertain disturbances. To cope with the two types of uncertainties, we combine backstepping methodology with adaptive neural design and nonlinear damping techniques. A smooth singularity-free adaptive neural controller is presented, where nonlinear damping terms are used to counteract the disturbances. The differentiability problem in controlling the disturbed strict-feedback system is solved without employing norm operation, which is usually used in robust control design. The proposed controllers can be applied to a large class of uncertain chaotic systems in practical situations. Simulation studies are conducted to verify the effectiveness of the scheme.

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