Identification of nonlinear hysteretic parameters by enhanced response sensitivity approach

Lu, Zhong-Rong; Yao, Renzhi; Liu, Jike

doi:10.1016/j.ijnonlinmec.2017.07.012

Cited by 31 publications

(13 citation statements)

References 28 publications

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“…To conclude, the dynamic equation of the structure with hysteresis can be described as follows (Lu et al, 2017),…”

Section: Modelling Structures With Hysteresismentioning

confidence: 99%

“…The gradient-based algorithms including the least-squares estimation (Smyth et al, 1999;Yang and Lin, 2004), the wavelet multi-resolution analysis (Chang and Shi, 2010) and the Levenberg-Marquardt algorithm (More´, 1978) require computation of the gradients. Just recently, Lu et al (2017) proposed a general methodology for hysteretic parameter identification within the sensitivity/gradient-based framework. In their work, only the first-order sensitivity analysis is involved and by introducing the trust-region constraint, the iterative solution is shown weakly convergent.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear hysteretic parameter identification using improved artificial bee colony algorithm

Yao

Chen

Wang

2021

Advances in Structural Engineering

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Hysteresis is a common phenomenon arising in many engineering applications. It describes a memory-based relation between the restoring force and the displacement. Identification of the hysteretic parameters is central to practical application of the hysteretic models. To proceed so, a noteworthy thing is that the hysteretic models are often complex and non-differentiable so that getting the gradients is never straightforward and therefore, the swarm-based algorithm is often preferable to inverse hysteretic parameter identification. Along these lines, an improved artificial bee colony algorithm is developed in this paper for general hysteretic parameter identification. On the one hand, several hysteretic models along with the extensions to tackle the degradation and pinching behaviours are considered and how to model a structure with hysteretic components is also elaborated. As a result, the governing equation for the direct problem is established. On the other hand, the differential evolution mechanism is introduced to improve the original artificial bee colony algorithm. Numerical examples are conducted to testify the feasibility and accuracy of the proposed method in nonlinear hysteretic parameter identification.

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“…To conclude, the dynamic equation of the structure with hysteresis can be described as follows (Lu et al, 2017),…”

Section: Modelling Structures With Hysteresismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nonlinear hysteretic parameter identification using improved artificial bee colony algorithm

Yao

Chen

Wang

2021

Advances in Structural Engineering

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“…[1][2][3] In this regard, two main categories can be recognized in the literature: online and offline methods. The idea behind these methods is to use the measured response of a structure (usually displacement, velocity, or acceleration) to estimate part of its unknown properties.…”

Section: Introductionmentioning

confidence: 99%

“…The idea behind these methods is to use the measured response of a structure (usually displacement, velocity, or acceleration) to estimate part of its unknown properties. [1][2][3] In this regard, two main categories can be recognized in the literature: online and offline methods. In the online methods, the estimation is done simultaneously with the measurements.…”

Section: Introductionmentioning

confidence: 99%

A new method for online identification of civil structures: Virtual synchronization

Ghaderi

Amini

2018

Adaptive Control & Signal

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This paper presents a new approach, named Virtual Synchronization Method (VSM), for online identification of stiffness and viscous damping in a civil structure while it is subjected to a harmonic ground motion acceleration. It is assumed that displacement and velocity of the structure relative to the ground are measured in real time. They are used to define a virtual system similar to the actual structure. Proper controllers and estimation functions are designed to force the states of this virtual system to follow those of the actual structure.Theoretical results are derived to study on what conditions, after the two systems synchronized, the estimation functions converge to the true stiffness and damping of the actual structure. Provided numerical examples show that VSM is a promising method for online identification of civil structures and should be the subject of further studies. KEYWORDS adaptive system identification, online identification of structures, real-time estimation of damping and stiffness, smart structures, Virtual Synchronization Method 16

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“…In the second set, identification of the nonlinear parameters from the measured data is formulated as an inverse problem and is often fulfilled by solving an optimization problem. Then, various techniques are proposed to deal with the state estimation problem or the optimization problem [2].…”

Section: Introductionmentioning

confidence: 99%

Identification of Linear and Nonlinear Parameters for Systems with Local Non-Linearity

HAN¹,

Zhang²

2018

dtmse

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A new method based on dynamic response sensitivity is proposed for the identification of local nonlinear system. The unknown local nonlinear hysteresis parameters are identified together with linear structural parameters. The sensitivities of structural dynamic response with respect to unknown parameters are derived. The identification equation is set up based on Taylor's first order approximation, and is solved with the damped least-squares method. A four-story shearing system with rubber isolation bearing of nonlinear hysteresis model is studied to validate the proposed method. Numerical simulation with noisy measured accelerations shows that the proposed method can accurately identify both linear and nonlinear parameters of the system. This method provides a new approach for detecting local nonlinear structures with incomplete measured output information.

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Identification of nonlinear hysteretic parameters by enhanced response sensitivity approach

Cited by 31 publications

References 28 publications

Nonlinear hysteretic parameter identification using improved artificial bee colony algorithm

Nonlinear hysteretic parameter identification using improved artificial bee colony algorithm

A new method for online identification of civil structures: Virtual synchronization

Identification of Linear and Nonlinear Parameters for Systems with Local Non-Linearity

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