Results 11 to 20 of about 128,037 (313)
Clamp Nonlinear Modeling and Hysteresis Model Parameter Identification [PDF]
IEEE Access, 2021 Based on the Bouc-Wen model, a nonlinear hysteretic restoring force model is established with dynamic equations. The hardening and softening of the material after reaching the yield limit are described by the nonlinear restoring force-displacement ...
Junzhe Lin +5 more
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The NARX Model-Based System Identification on Nonlinear, Rotor-Bearing Systems
Applied Sciences, 2017 In practice, it is usually difficult to obtain the physical model of nonlinear, rotor-bearing systems due to uncertain nonlinearities. In order to solve this issue to conduct the analysis and design of nonlinear, rotor-bearing systems, in this study, a ...
Ying Ma +4 more
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Research on Adaptive Model Predictive Control Algorithm for Remotely Operated Vehicle
Kongzhi Yu Xinxi Jishu, 2023 Aiming at the motion state coupling and model non-linearity of remotely operated vehicle (ROV) caused by the asymmetric structural layout of ROV and changes of center of gravity and center of buoyancy, this paper proposes a model identification algorithm
ZHU Yinggu +3 more
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Upgrading Behavioral Models for the Design of Digital Predistorters
Sensors, 2021 This work presents a strategy to upgrade models for power amplifier (PA) behavioral modeling and digital predistortion (DPD). These incomplete structures are the consequence of nonlinear order and memory depth model truncation with the purpose of ...
Carlos Crespo-Cadenas +2 more
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A Bivariate Volterra Series Model for the Design of Power Amplifier Digital Predistorters
Sensors, 2021 The operation of the power amplifier (PA) in wireless transmitters presents a trade-off between linearity and power efficiency, being more efficient when the device exhibits the highest nonlinearity.
Carlos Crespo-Cadenas +2 more
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Identification of Nonlinear Latent Hierarchical Models
Advances in Neural Information Processing Systems 36, 2023 Identifying latent variables and causal structures from observational data is essential to many real-world applications involving biological data, medical data, and unstructured data such as images and languages. However, this task can be highly challenging, especially when observed variables are generated by causally related latent variables and the ...
Lingjing Kong +5 more
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Model parameter on-line identification with nonlinear parametrization – manipulator model
Technical Transactions, 2022 This paper presents an example of solving the parameter identification problem in the case of a robot with two degrees of freedom. In this study, a weighted recursive least squares algorithm was generalised to a case of nonlinear parameterisation in ...
Cedro Leszek
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The identification method of the coal mill motor power model with the use of machine learning techniques [PDF]
Bulletin of the Polish Academy of Sciences: Technical Sciences, 1921 The article presents an identification method of the model of the ball-and-race coal mill motor power signal with the use of machine learning techniques. The stages of preparing training data for model parameters identification purposes are described, as
Zofia Magdalena Łabęda-Grudziak +1 more
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Automatika, 2022 This paper studies the modelling of a class of nonlinear plants with known structures but unknown parameters and proposes a general nonlinear U-model expression. The particle swarm optimization algorithm is used to identify the time-varying parameters of
Fengxia Xu +3 more
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A novel strategy for force identification of nonlinear structures
Journal of Low Frequency Noise, Vibration and Active Control, 2022 Dynamic force is the key indicator for monitoring the condition of a mechanical product. These mechanical structures always encompass some nonlinear factors. Most previous studies focused on obtaining the dynamic force of linear structures. Consequently,
Jie Liu +3 more
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