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2023 | OriginalPaper | Chapter

8. Reinforcement Learning Based Weighting Factors’ Real-Time Updating Scheme for the FCS Model Predictive Control to Improve the Large-Signal Stability of Inverters

Authors : Xin Zhang, Jinsong He, Hao Ma, Zhixun Ma, Xiaohai Ge

Published in: Stability Enhancement Methods of Inverters Based on Lyapunov Function, Predictive Control, and Reinforcement Learning

Publisher: Springer Nature Singapore

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Abstract

The previous chapter demonstrates that the finite control set (FCS) model predictive control.

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previous chapter Composite-Bisection Predictive Control to Stabilize the Three Phase Inverter Cascaded with Input EMI Filter in the SPS
Literature
1.
S. Vazquez et al., “Model predictive control: A review of its applications in power electronics,” IEEE Ind. Electron. Mag., vol. 8, no. 1, pp. 16–31, 2014.CrossRef
2.
S. Vazquez, J. Rodriguez, M. Rivera, L. G. Franquelo, and M. Norambuena, “Model Predictive Control for Power Converters and Drives: Advances and Trends,” IEEE Trans. Ind. Electron., vol. 64, no. 2, pp. 935–947, 2017.CrossRef
3.
Z. Ma, Z. Xin, J. He, and Z. Zeng, “Robust Constant Switching Frequency Predictive Current Control with a Dichotomy Solution for Three-Phase Grid-Connected Inverters,” in 2018 IEEE Energy Conversion Congress and Exposition (ECCE), 2018, pp. 5282–5285.
4.
J. He, X. Zhang, H. Ma, and C. Cai, “Lyapunov-based Large-signal Control of Three- phase Stand-alone Inverters with Inherent Dual Control Loops and Load Disturbance Adaptivity,” IEEE Trans. Ind. Electron., vol. 68, no. 9, pp. 8391–8401, 2020.CrossRef
5.
J. Huang, F. Guo, C. Wen, B. Yang, and J. Xiao, “A direct power control strategy for AC/DC converter based on best switching state approach,” IEEE J. Emerg. Sel. Top. Power Electron., vol. 6, no. 4, pp. 2273–2286, 2018.CrossRef
6.
H. Komurcugil, S. Member, N. Altin, and S. Ozdemir, “Lyapunov-Function and Proportional-Resonant-Based Control Strategy for Single-Phase Grid-Connected VSI With LCL Filter,” IEEE Trans. Ind. Electron., vol. 63, no. 5, pp. 2838–2849, 2016.CrossRef
7.
J. He, C. C. Y. John, X. Zhang, Z. Li, and Z. Liu, “An Adaptive Dual-loop Lyapunov-based Control Scheme for a Single-Phase UPS Inverter,” IEEE Trans. Power Electron., vol. 35, no. 9, pp. 8886–8891, 2020.CrossRef
8.
X. Li, J. He, C. Wen, and X. Liu, “Backstepping Based Adaptive Control of a Class of Uncertain Incommensurate Fractional-Order Nonlinear Systems with External Disturbance,” IEEE Trans. Ind. Electron., vol. 69, no. 4, pp. 4087–4095, 2022.CrossRef
9.
J. He and X. Zhang, “An Ellipse-optimized Composite Backstepping Control Strategy for a Point-of-load Inverter Under Load Disturbance in the Shipboard Power System,” IEEE Open J. Power Electron., vol. 1, no. 8, pp. 420–430, 2020.CrossRef
10.
S. Jiang, D. Cao, Y. Li, J. Liu, and F. Z. Peng, “Low-THD, fast-transient, and cost-effective synchronous-frame repetitive controller for three-phase UPS inverters,” IEEE Trans. Power Electron., vol. 27, no. 6, pp. 2994–3005, 2012.CrossRef
11.
P. Cortés et al., “Guidelines for weighting factors design in model predictive control of power converters and drives,” Proc. IEEE Int. Conf. Ind. Technol., pp. 1–7, 2009.
12.
P. Zanchetta, “Heuristic multi-objective optimization for cost function weights selection in finite states model predictive control,” Preced. 2011 - Work. Predict. Control Electr. Drives Power Electron., pp. 70–75, 2011.
13.
S. A. Davari, D. A. Khaburi, and R. Kennel, “An improved FCS-MPC algorithm for an induction motor with an imposed optimized weighting factor,” IEEE Trans. Power Electron., vol. 27, no. 3, pp. 1540–1551, 2012.CrossRef
14.
F. Villarroel, J. R. Espinoza, C. A. Rojas, J. Rodriguez, M. Rivera, and D. Sbarbaro, “Multiobjective switching state selector for finite-states model predictive control based on fuzzy decision making in a matrix converter,” IEEE Trans. Ind. Electron., vol. 60, no. 2, pp. 589–599, 2013.CrossRef
15.
T. Dragičević and M. Novak, “Weighting Factor Design in Model Predictive Control of Power Electronic Converters: An Artificial Neural Network Approach,” IEEE Trans. Ind. Electron., vol. 66, no. 11, pp. 8870–8880, 2019.CrossRef
16.
M. Novak, T. Dragicevic, and F. Blaabjerg, “Weighting factor design based on artificial neural network for finite set MPC operated 3L-NPC converter,” Conf. Proc. - IEEE Appl. Power Electron. Conf. Expo. - APEC, vol. 2019-March, pp. 77–82, 2019.
17.
Z. Ma, X. Zhang, J. Huang, and B. Zhao, “Stability-constraining-dichotomy-solution-based model predictive control to improve the stability of power conversion system in the MEA,” IEEE Trans. Ind. Electron., vol. 66, no. 7, pp. 5696–5706, 2019.CrossRef
18.
T. Dragičević, “Dynamic Stabilization of DC Microgrids with Predictive Control of Point-of-Load Converters,” IEEE Trans. Power Electron., vol. 33, no. 12, pp. 10872–10884, 2018.CrossRef
19.
J. He, C. Wen, and X. Zhang, “Composite-Bisection Predictive Control to Stabilize and Indirectly Regulate Downstream Load Inverters Cascaded With LC Input Filters in the SPS,” IEEE J. Emerg. Sel. Top. Power Electron., vol. 9, no. 6, pp. 6854–6863, Dec. 2021.CrossRef
20.
P. Cortes, J. Rodriguez, C. Silva, and A. Flores, “Delay compensation in model predictive current control of a three-phase inverter,” IEEE Trans. Ind. Electron., vol. 59, no. 2, pp. 1323–1325, 2012.CrossRef
21.
J. He, L. Xing, and C. Wen, “Weighting Factors’ Real-time Updating for Finite Control Set Model Predictive Control of Power Converters via Reinforcement Learning,” in 2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA), 2021, pp. 707–712.
22.
23.
T. P. Lillicrap et al., “Continuous control with deep reinforcement learning,” 4th Int. Conf. Learn. Represent. ICLR 2016 - Conf. Track Proc., Sep. 2016.
24.
T. Dragicevic, P. Wheeler, and F. Blaabjerg, “Artificial Intelligence Aided Automated Design for Reliability of Power Electronic Systems,” IEEE Trans. Power Electron., vol. 34, no. 8, pp. 7161–7171, 2019.CrossRef
Metadata
Title
Reinforcement Learning Based Weighting Factors’ Real-Time Updating Scheme for the FCS Model Predictive Control to Improve the Large-Signal Stability of Inverters
Authors
Xin Zhang
Jinsong He
Hao Ma
Zhixun Ma
Xiaohai Ge
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Stability Enhancement Methods of Inverters Based on Lyapunov Function, Predictive Control, and Reinforcement Learning

Print ISBN: 978-981-19-7190-7

Electronic ISBN: 978-981-19-7191-4

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-19-7191-4_8