Adaptive Backstepping Fuzzy Neural Controller Based on Fuzzy Sliding Mode of Active Power Filter

被引：26
|
作者：
Fang, Yunmei [1 ]
Fei, Juntao [2 ,3 ]
Wang, Tengteng [2 ]
机构：
[1] Hohai Univ, Coll Mech & Elect Engn, Changzhou 213022, Jiangsu, Peoples R China
[2] Hohai Univ, Coll IoT Engn, Changzhou 213022, Jiangsu, Peoples R China
[3] Jiangsu Key Lab Power Transmiss & Distribut Equip, Changzhou 213022, Jiangsu, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷 / 08期
基金：
美国国家科学基金会;
关键词：
Active filters; Fuzzy control; Fuzzy neural networks; Backstepping; Adaptive systems; Power harmonic filters; Harmonic analysis; Fuzzy neural network; adaptive fuzzy control; backstepping control; active power filter; COMPENSATION;
D O I：
10.1109/ACCESS.2020.2995755
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An adaptive backstepping fuzzy neural network (FNN) controller using a fuzzy sliding mode controller is designed to suppress the harmonics and improve the performance of a shunt active power filter (APF). A backstepping method transforms the APF system into a series of subsystems and uses the virtual control to simplify the controller design. A FNN controller is utilized to approach the nonlinear APF system. An adaptive fuzzy system is employed to adjust the sliding gain to compensate the approximation error of neural network and diminish the chattering. The weights of the fuzzy neural network and fuzzy system parameters are adjusted in real-time to guarantee the asymptotic stability of the designed control system. Simulation and experiemental studies indicate the validitiy of the proposed control method, demonstrating the good compensation performance and strong robustness.
引用
收藏
页码：96027 / 96035
页数：9
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