DocumentCode :
3034253
Title :
Neural Network Control Techniques of Hybrid Active Power Filter
Author :
You-hua Jiang ; Yong-Wei Chen
Author_Institution :
Sch. of Comput. & Inf. Technol., Shanghai Univ. of Electr. Power, Shanghai, China
Volume :
4
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
26
Lastpage :
30
Abstract :
A multi-object optimization approach was developed for the design of hybrid active power filters (HAPF) to give better mitigation of the harmonics and better reactive power compensation. The neural network technique was used with optimization theory to improve the algorithm precision and stability. The optimization is more effective since the performance goals and optimization parameters were optimized together. Secondly, this paper presents the design of a hierarchical fuzzy current control scheme for a shunt active power filter compared with a single fuzzy controller scheme. It provides superior current tracking capability and switch frequency signal is limit in the permit range. Finally, many simulations and experimental result demonstrate the validity of the theory.
Keywords :
active filters; electric current control; fuzzy control; neurocontrollers; optimisation; power filters; reactive power control; hierarchical fuzzy current control scheme; hybrid active power filter; multi-object optimization; neural network control; reactive power compensation; shunt active power filter; Active filters; Current control; Design optimization; Fuzzy control; Neural networks; Power harmonic filters; Power system harmonics; Reactive power; Stability; Switches; hierarchical fuzzy current control; hybrid active power filters; multi-object optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
Type :
conf
DOI :
10.1109/AICI.2009.296
Filename :
5376898
Link To Document :
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