Output-only structural parameter identification with evolutionary algorithms and correlation functions

Wang, Xiaojuan; Zhang, Guangcai; Wang, Xiaomei; Ni, Pinghe

doi:10.1088/1361-665x/ab6ce9

Cited by 16 publications

(4 citation statements)

References 36 publications

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“…The inverse identification of elastic properties of composite materials was carried out using a hybrid GA-ACO-PSO algorithm in [18]. The structural parameter identification with evolutionary algorithms and correlation functions was carried out in [19]. A hybrid identification method in [20] is applied to structural health monitoring to detect the reduction of stiffness with limited sensors and contaminated measurements by applying evolutionary algorithms.…”

Section: Of 12mentioning

confidence: 99%

Parameter Identification of Flexible Link Manipulators Using Evolutionary Algorithms

Lara-Molina

2024

Preprint

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This paper addresses the parameter identification of a one-link flexible manipulator based on the experimental measurement of the inputs/outputs, the finite element model, and the application of evolutionary algorithms. A novel approach is proposed to find the values of inertia, stiffness, and damping parameters by minimizing the difference between the numerical model’s outputs and the testbed’s outputs, considering the joint position and acceleration of the link’s tip. The dynamic model is initially obtained using the finite element method and the Lagrange principle. A prototype of a single one-link flexible manipulator is used in the experimental application wherein the servomotor applies the input torque, and the outputs are the joint angle and the link’s tip acceleration. Then, an optimization problem minimizes the difference between numerical and experimental outputs to determine the set of parameters using evolutionary algorithms. A comparative analysis to obtain the identified parameters is established using genetic algorithms, particle swarm optimization, and differential evolution. The proposed identification approach permitted the determination of the dynamic parameters based on the complete dynamic model of the flexible-link manipulator, which is different from the approaches reported in the literature that identify a simplified model. This information is essential for the design of the motion and vibration control laws.

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Section: Of 12mentioning

confidence: 99%

Parameter Identification of Flexible Link Manipulators Using Evolutionary Algorithms

Lara-Molina

2024

Preprint

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“…The unknown structural parameter can be identified from genetic algorithm, 27 particle swarm optimization, 31 sensitivity method, 23,28,29 and Kalman filter. [14][15][16][17] The unknown input force can be identified with regularization method and probabilistic methods.…”

Section: Equation Of Motion and Output-only Damage Identificationmentioning

confidence: 99%

An output‐only structural condition assessment method for civil structures by the stochastic gradient descent method

Ding

2022

Structural Contr & Hlth

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The interesting to assess the condition of a structure with structural health monitoring data has gained many attentions. Most of the existing methods require the measurement at the force location. This paper presents a novel output-only condition assessment method that does not require measurement at the force location. The unknown structural damage indices and input force can be identified with the stochastic gradient descent method. The dynamic acceleration response sensitivities with respect to the unknown structural damage indices and input force are derived analytically. Both unknown damage indices and unknown input force can be identified by minimizing the discrepancy between the measured and calculated vibration data. Numerical studies on a two-dimensional truss and seven-floor frame and experimental studies on a steel frame structure are presented to verify the accuracy and efficiency of the proposed method. Results demonstrate that the damage severity, location, and unknown input force can be identified. Also, the measurement at the force location is not required. Furthermore, when 20% measurement noise is considered, the identified error is less than 5%.

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“…The inverse identification of elastic properties of composite materials was carried out using a hybrid GA-ACO-PSO algorithm in [23]. The structural parameter identification with evolutionary algorithms and correlation functions was carried out in [24]. A hybrid identification method in [25] was applied to structural health monitoring to detect the reduction of stiffness with limited sensors and contaminated measurements by applying evolutionary algorithms.…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification of Flexible Link Manipulators Using Evolutionary Algorithms

Lara-Molina

2024

Machines

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This paper addresses the parameter identification of a one-link flexible manipulator based on the experimental measurement of the inputs/outputs, the finite element model, and the application of evolutionary algorithms. A novel approach is proposed to find the values of inertia, stiffness, and damping parameters by minimizing the difference between the numerical model’s outputs and the testbed’s outputs, thus considering the joint position and acceleration of the link’s tip. The dynamic model is initially obtained using the finite element method and the Lagrange principle. A prototype of a single one-link flexible manipulator is used in the experimental application, wherein the servomotor applies the input torque, and the outputs are the joint angle and the link’s tip acceleration. Then, an optimization problem minimizes the difference between the numerical and experimental outputs to determine the set of parameters using evolutionary algorithms. A comparative analysis to obtain the identified parameters is established using genetic algorithms, particle swarm optimization, and differential evolution. The proposed identification approach permitted the determination of the dynamic parameters based on the complete dynamic model of the flexible-link manipulator, which is different from the approaches reported in the literature that identify a simplified model. This information is essential for the design of the motion and vibration control laws.

show abstract

Output-only structural parameter identification with evolutionary algorithms and correlation functions

Cited by 16 publications

References 36 publications

Parameter Identification of Flexible Link Manipulators Using Evolutionary Algorithms

Parameter Identification of Flexible Link Manipulators Using Evolutionary Algorithms

An output‐only structural condition assessment method for civil structures by the stochastic gradient descent method

Parameter Identification of Flexible Link Manipulators Using Evolutionary Algorithms

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