Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer

Liu Zhile; Xie Yunyi; Wang Dan

doi:doi:10.11648/j.sd.20221006.14

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Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer

Liu Zhile, Xie Yunyi, Wang Dan

Published in Science Discovery (Volume 10, Issue 6)

Received: 19 October 2022 Accepted: 10 November 2022 Published: 14 November 2022

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Abstract

Aiming at the problem of low control accuracy and delay compensation failure of the finite control set model predictive current control (FCS-MPCC) under parameter variation and external disturbances of the grid - connected inverter, a hyper-local model extended state observer (An Ultra-local model extended state observer (U-ESO) based predictive control method is proposed. As the nonlinear fal function in the extended state observer (ESO) requires more parameters to be adjusted, the U-ESO is used to estimate the total set perturbation error to correct the state variables in real time, and the corrected state variables are combined with the override control to act on the prediction model, and only the inputs and outputs of the system are used in the control process, which effectively reduces the complexity of the control parameters In addition, the value function of the prediction model is reconstructed to reduce the control delay of the system, the control parameters are designed using frequency domain analysis to improve the control performance, and the stability of the prediction model is demonstrated using Lyapunov stability criterion. The effectiveness of using U-ESO to compensate the control delay of FCS-MPCC under parameter perturbation is verified by MATLAB/Simulink. Compared with the traditional ESO, U-ESO can simplify the design of the observer and avoid the complicated parameter rectification process, while solving the problem of delay compensation failure in the process of parameter perturbation, improving the dynamic response speed, and having strong anti-interference and Robustness.

Published in	Science Discovery (Volume 10, Issue 6)
DOI	10.11648/j.sd.20221006.14
Page(s)	396-405
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Time Delay Compensation, Parameter Calibration, Extended State Observer, Model Predictive Control, Grid-Connected Inverter, Stability

References

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[3]	贾冠龙, 李冬辉, 姚乐乐. 改进有限集模型预测控制策略在三相级联并网逆变器中的应用 [J]. 电网技术, 2017, 41 (1): 245-250.
[4]	程俊, 肖先勇, 马俊鹏, 等. 三相储能型准Z源并网逆变器有限开关序列模型预测直接功率控制 [J]. 电网技术, 2020, 44 (05): 1647-1655.
[5]	Cortes, Patricio, Rodriguez, et al. Delay Compensation in Model Predictive Current Control of a Three-Phase Inverter [J]. IEEE Transactions on Industrial Electronics, 2012, 59 (2): 1323-1325.
[6]	Pan Donghua, Ruan Xinbo, Bao Chenlei, et al. Capacitor – Current - Feedback Active Damping With Reduced Computation Delay for Improving Robustness of LCL - Type Grid-Connected Inverter [J]. IEEE Transactions on Power Electronics, 2014, 29 (7): 3414-3427.
[7]	Wang Hanwei, Zhang Hui. Study on an Improve Finite - Control - Set - Model Predictive Control (FCS - MPC) Strategy for a T - Type Rectifier with Direct Power Control Strategy [J]. IEEJ Transactions on Electrical and Electronic Engineering, 2021.
[8]	杨苓, 罗安, 陈燕东, 等. LCL型逆变器的鲁棒延时补偿并网控制方法及其稳定性分析 [J]. 电网技术, 2015, 39 (11): 3102-3108.
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[10]	Lee K J, Park B G, Kim R Y, et al. Robust Predictive Current Controller Based on a Disturbance Estimator in a Three - Phase Grid - Connected Inverter [J]. IEEE Transactions on Power Electronics, 2012, 27 (1): 276-283.
[11]	Young H A, Perez M A, Rodriguez J. Analysis of Finite-Control-Set Model Predictive Current Control with Model Parameter Mismatch in a Three - Phase Inverter [J]. IEEE Transactions on Industrial Electronics, 2016, 63 (5): 3100-3107.
[12]	Wang Yingjie, Wang Chao, Zeng Wei, et al. Multifactorial Prediction Errors Analysis and a Feedback Self - Correction on Model Predictive Control for the Three - Phase Inverter [J]. IEEE Transactions on Industrial Electronics, 2019, 66 (5): 3647-3654.
[13]	杨林, 曾江, 黄仲龙. 线性自抗扰技术在LCL逆变器并网电流控制及有源阻尼中的应用 [J]. 电网技术, 2019, 43 (4): 1378-1386.
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APA Style

Liu Zhile, Xie Yunyi, Wang Dan. (2022). Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer. Science Discovery, 10(6), 396-405. https://doi.org/10.11648/j.sd.20221006.14

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ACS Style

Liu Zhile; Xie Yunyi; Wang Dan. Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer. Sci. Discov. 2022, 10(6), 396-405. doi: 10.11648/j.sd.20221006.14

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AMA Style

Liu Zhile, Xie Yunyi, Wang Dan. Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer. Sci Discov. 2022;10(6):396-405. doi: 10.11648/j.sd.20221006.14

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@article{10.11648/j.sd.20221006.14,
  author = {Liu Zhile and Xie Yunyi and Wang Dan},
  title = {Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer},
  journal = {Science Discovery},
  volume = {10},
  number = {6},
  pages = {396-405},
  doi = {10.11648/j.sd.20221006.14},
  url = {https://doi.org/10.11648/j.sd.20221006.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20221006.14},
  abstract = {Aiming at the problem of low control accuracy and delay compensation failure of the finite control set model predictive current control (FCS-MPCC) under parameter variation and external disturbances of the grid - connected inverter, a hyper-local model extended state observer (An Ultra-local model extended state observer (U-ESO) based predictive control method is proposed. As the nonlinear fal function in the extended state observer (ESO) requires more parameters to be adjusted, the U-ESO is used to estimate the total set perturbation error to correct the state variables in real time, and the corrected state variables are combined with the override control to act on the prediction model, and only the inputs and outputs of the system are used in the control process, which effectively reduces the complexity of the control parameters In addition, the value function of the prediction model is reconstructed to reduce the control delay of the system, the control parameters are designed using frequency domain analysis to improve the control performance, and the stability of the prediction model is demonstrated using Lyapunov stability criterion. The effectiveness of using U-ESO to compensate the control delay of FCS-MPCC under parameter perturbation is verified by MATLAB/Simulink. Compared with the traditional ESO, U-ESO can simplify the design of the observer and avoid the complicated parameter rectification process, while solving the problem of delay compensation failure in the process of parameter perturbation, improving the dynamic response speed, and having strong anti-interference and Robustness.},
 year = {2022}
}

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TY  - JOUR
T1  - Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer
AU  - Liu Zhile
AU  - Xie Yunyi
AU  - Wang Dan
Y1  - 2022/11/14
PY  - 2022
N1  - https://doi.org/10.11648/j.sd.20221006.14
DO  - 10.11648/j.sd.20221006.14
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 396
EP  - 405
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20221006.14
AB  - Aiming at the problem of low control accuracy and delay compensation failure of the finite control set model predictive current control (FCS-MPCC) under parameter variation and external disturbances of the grid - connected inverter, a hyper-local model extended state observer (An Ultra-local model extended state observer (U-ESO) based predictive control method is proposed. As the nonlinear fal function in the extended state observer (ESO) requires more parameters to be adjusted, the U-ESO is used to estimate the total set perturbation error to correct the state variables in real time, and the corrected state variables are combined with the override control to act on the prediction model, and only the inputs and outputs of the system are used in the control process, which effectively reduces the complexity of the control parameters In addition, the value function of the prediction model is reconstructed to reduce the control delay of the system, the control parameters are designed using frequency domain analysis to improve the control performance, and the stability of the prediction model is demonstrated using Lyapunov stability criterion. The effectiveness of using U-ESO to compensate the control delay of FCS-MPCC under parameter perturbation is verified by MATLAB/Simulink. Compared with the traditional ESO, U-ESO can simplify the design of the observer and avoid the complicated parameter rectification process, while solving the problem of delay compensation failure in the process of parameter perturbation, improving the dynamic response speed, and having strong anti-interference and Robustness.
VL  - 10
IS  - 6
ER  -

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Author Information

Liu Zhile

School of Electrical and Control Engineering, Liaoning Technical University, Huludao, China
Xie Yunyi

CATARC Automotive Inspection Center (Wuhan) Co., Ltd, Wuhan, China
Wang Dan

School of Electrical and Information Engineering, Hubei Institute of Automotive Technology, Shiyan, China

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Plain Text BibTeX RIS

APA Style

Liu Zhile, Xie Yunyi, Wang Dan. (2022). Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer. Science Discovery, 10(6), 396-405. https://doi.org/10.11648/j.sd.20221006.14

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ACS Style

Liu Zhile; Xie Yunyi; Wang Dan. Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer. Sci. Discov. 2022, 10(6), 396-405. doi: 10.11648/j.sd.20221006.14

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AMA Style

Liu Zhile, Xie Yunyi, Wang Dan. Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer. Sci Discov. 2022;10(6):396-405. doi: 10.11648/j.sd.20221006.14

Copy | Download

@article{10.11648/j.sd.20221006.14,
  author = {Liu Zhile and Xie Yunyi and Wang Dan},
  title = {Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer},
  journal = {Science Discovery},
  volume = {10},
  number = {6},
  pages = {396-405},
  doi = {10.11648/j.sd.20221006.14},
  url = {https://doi.org/10.11648/j.sd.20221006.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20221006.14},
  abstract = {Aiming at the problem of low control accuracy and delay compensation failure of the finite control set model predictive current control (FCS-MPCC) under parameter variation and external disturbances of the grid - connected inverter, a hyper-local model extended state observer (An Ultra-local model extended state observer (U-ESO) based predictive control method is proposed. As the nonlinear fal function in the extended state observer (ESO) requires more parameters to be adjusted, the U-ESO is used to estimate the total set perturbation error to correct the state variables in real time, and the corrected state variables are combined with the override control to act on the prediction model, and only the inputs and outputs of the system are used in the control process, which effectively reduces the complexity of the control parameters In addition, the value function of the prediction model is reconstructed to reduce the control delay of the system, the control parameters are designed using frequency domain analysis to improve the control performance, and the stability of the prediction model is demonstrated using Lyapunov stability criterion. The effectiveness of using U-ESO to compensate the control delay of FCS-MPCC under parameter perturbation is verified by MATLAB/Simulink. Compared with the traditional ESO, U-ESO can simplify the design of the observer and avoid the complicated parameter rectification process, while solving the problem of delay compensation failure in the process of parameter perturbation, improving the dynamic response speed, and having strong anti-interference and Robustness.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Model Predictive Control of Grid-Connected Inverter Based on Exponentially Extended State Observer
AU  - Liu Zhile
AU  - Xie Yunyi
AU  - Wang Dan
Y1  - 2022/11/14
PY  - 2022
N1  - https://doi.org/10.11648/j.sd.20221006.14
DO  - 10.11648/j.sd.20221006.14
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 396
EP  - 405
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20221006.14
AB  - Aiming at the problem of low control accuracy and delay compensation failure of the finite control set model predictive current control (FCS-MPCC) under parameter variation and external disturbances of the grid - connected inverter, a hyper-local model extended state observer (An Ultra-local model extended state observer (U-ESO) based predictive control method is proposed. As the nonlinear fal function in the extended state observer (ESO) requires more parameters to be adjusted, the U-ESO is used to estimate the total set perturbation error to correct the state variables in real time, and the corrected state variables are combined with the override control to act on the prediction model, and only the inputs and outputs of the system are used in the control process, which effectively reduces the complexity of the control parameters In addition, the value function of the prediction model is reconstructed to reduce the control delay of the system, the control parameters are designed using frequency domain analysis to improve the control performance, and the stability of the prediction model is demonstrated using Lyapunov stability criterion. The effectiveness of using U-ESO to compensate the control delay of FCS-MPCC under parameter perturbation is verified by MATLAB/Simulink. Compared with the traditional ESO, U-ESO can simplify the design of the observer and avoid the complicated parameter rectification process, while solving the problem of delay compensation failure in the process of parameter perturbation, improving the dynamic response speed, and having strong anti-interference and Robustness.
VL  - 10
IS  - 6
ER  -

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