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Neural-Network-Based Terminal Sliding Mode Control for Frequency Stabilization of Renewable Power Systems

Dianwei Qian Guoliang Fan

自动化学报（英文版）2018，Vol.5Issue(3)：706-717,12.

自动化学报（英文版）2018，Vol.5Issue(3)：706-717,12.DOI:10.1109/JAS.2018.7511078

Neural-Network-Based Terminal Sliding Mode Control for Frequency Stabilization of Renewable Power Systems

Dianwei Qian ¹Guoliang Fan²

作者信息

1. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
2. Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
折叠

摘要

关键词

Generation rate constraint (GRC)/load frequency control (LFC)/radial basis function neural networks (RBF NNs)/renewable power system/terminal sliding mode control (T-SMC)

Key words

Generation rate constraint (GRC)/load frequency control (LFC)/radial basis function neural networks (RBF NNs)/renewable power system/terminal sliding mode control (T-SMC)

引用本文复制引用

Dianwei Qian,Guoliang Fan..Neural-Network-Based Terminal Sliding Mode Control for Frequency Stabilization of Renewable Power Systems[J].自动化学报（英文版）,2018,5(3):706-717,12.

基金项目

This work was supported by National Natural Science Foundation of China (60904008,61273336),the Fundamental Research Funds for the Central Universities (2018MS025),and the National Basic Research Program of China (973 Program) (B1320133020). （60904008,61273336）

自动化学报（英文版）

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ISSN：2329-9266

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