Adaptive Repetitive Learning Control of PMSM Servo Systems with Bounded Nonparametric Uncertainties: Theory and Experiments

Chen, Qiang; X, Yu; Sun, Mingxuan; Wu, Chun; Zhang, Fu

doi:10.1109/tie.2020.3016257

Cited by 74 publications

(42 citation statements)

References 31 publications

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“…To overcome this limitation, we derived estimation equations for the value ranges of relevant experimental metrics—mixed potential, apparent first-order reaction rate of cobalt removal, equilibrium concentration, and attenuation coefficient for the apparent consumption rate of hydrogen ions—based on model simplification assumptions in the constraint construction process. These equations linked the experimental phenomenon metrics to the model parameters providing deeper insights into the model parameters adjustment for model users and controller design [ 22 , 23 ].…”

Section: Discussionmentioning

confidence: 99%

Constrained Parameter Estimation for a Mechanistic Kinetic Model of Cobalt–Hydrogen Electrochemical Competition during a Cobalt Removal Process

Liang

Zhang

2021

Entropy

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A mechanistic kinetic model of cobalt–hydrogen electrochemical competition for the cobalt removal process in zinc hydrometallurgical was proposed. In addition, to overcome the parameter estimation difficulties arising from the model nonlinearities and the lack of information on the possible value ranges of parameters to be estimated, a constrained guided parameter estimation scheme was derived based on model equations and experimental data. The proposed model and the parameter estimation scheme have two advantages: (i) The model reflected for the first time the mechanism of the electrochemical competition between cobalt and hydrogen ions in the process of cobalt removal in zinc hydrometallurgy; (ii) The proposed constrained parameter estimation scheme did not depend on the information of the possible value ranges of parameters to be estimated; (iii) the constraint conditions provided in that scheme directly linked the experimental phenomenon metrics to the model parameters thereby providing deeper insights into the model parameters for model users. Numerical experiments showed that the proposed constrained parameter estimation algorithm significantly improved the estimation efficiency. Meanwhile, the proposed cobalt–hydrogen electrochemical competition model allowed for accurate simulation of the impact of hydrogen ions on cobalt removal rate as well as simulation of the trend of hydrogen ion concentration, which would be helpful for the actual cobalt removal process in zinc hydrometallurgy.

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Section: Discussionmentioning

confidence: 99%

Constrained Parameter Estimation for a Mechanistic Kinetic Model of Cobalt–Hydrogen Electrochemical Competition during a Cobalt Removal Process

Liang

Zhang

2021

Entropy

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“…From equations ( 13), (30), and (31), the positioning error model after the rotary deformation Δc i is derived as follows:…”

Section: Modelling Of Radial Deformationmentioning

confidence: 99%

“…Finally, since C a and C r are the integrated stiffness, they cannot be obtained directly by measurement. However, many mathematical methods can be used to identify C a and C r , e.g., least square method [29,30], genetic algorithm [31], particle swarm optimization algorithm [32], Kalman filtering algorithm [33], etc.…”

Section: Error Modelling Including Axial and Radial Deformationmentioning

confidence: 99%

Positioning Error Compensation for Industrial Robots Based on Stiffness Modelling

Gao

Liu

2020

Complexity

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Insufficient stiffness of industrial robots is a significant factor which affects its positioning accuracy. To improve the positioning accuracy, a novel positioning error compensation method based on the stiffness modelling is proposed in this paper. First, the positioning errors considering the end load and gravity of industrial robots due to stiffness are analyzed. Based on the results of analysis, it is found that the positioning errors can be described by two kinds of deformation errors at joints: the axial deformation error and the radial deformation error. Then, the axial deformation error is modelled by the differential relationship of kinematics equations. The model of radial deformation error is deduced through the recurrence method and rotation transformation between joints. Finally, these two models are transformed into a Cartesian coordinate system, and a positioning error compensation method based on these two models is presented. Simulations based on the finite element analysis are implemented to verify the positioning error compensation method. The results show that the suggested method can efficiently predict the positioning error according to the gravity and loads, so that the positioning accuracy of industrial robots can be improved with the proposed method.

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“…Chou et al [19] used the function method to achieve curve fitting and established a regression function model, which provides a good approach and reference for us. e adaptive repetitive learning control and the predefined time sliding mode control proposed by Wang et al [20,21] provide good research ideas for us. When the vehicle is passing, the overall state of the ballast bed is relatively no mutation, so the parameter values of the dynamic characteristics are relatively unchanged.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Parameter Optimization of Dynamic Characteristic Variables of Ballast Bed during Operation for Dynamic Track Stabilizer

Yan

Yang

2021

Complexity

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The high traffic density of railway line causes ballasted track to be extremely busy, and thus it is particularly important to improve the efficiency during railway maintenance. The changing law of dynamic characteristics of ballast bed during operation for the dynamic track stabilizer is conducive to optimize simulation analysis of the vehicle-track system, so as to provide an optimized choice of operating parameters for promoting the pertinence and efficiency of dynamic track stabilizer. This paper presents the acceleration response of vehicle-track-subgrade system during operation of a WD-320 dynamic track stabilizer and proposes the range of effective operating parameters. Then, the influence of operating parameters on the dynamic characteristics of the ballast bed is discussed for searching the optimal operating parameters under the single factor influence. Finally, the change laws including the support stiffness, damping, lateral resistance, and subsidence for the ballast bed are studied, and a parameterized model for dynamic characteristics of the ballast bed which can optimize the selection for operating parameters is constructed, rendering an effective reference variable for improving the simulation accuracy of the vehicle-track coupling system.

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Adaptive Repetitive Learning Control of PMSM Servo Systems with Bounded Nonparametric Uncertainties: Theory and Experiments

Cited by 74 publications

References 31 publications

Constrained Parameter Estimation for a Mechanistic Kinetic Model of Cobalt–Hydrogen Electrochemical Competition during a Cobalt Removal Process

Constrained Parameter Estimation for a Mechanistic Kinetic Model of Cobalt–Hydrogen Electrochemical Competition during a Cobalt Removal Process

Positioning Error Compensation for Industrial Robots Based on Stiffness Modelling

Modeling and Parameter Optimization of Dynamic Characteristic Variables of Ballast Bed during Operation for Dynamic Track Stabilizer

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