DocumentCode :
2276097
Title :
An adaptive Neuro-Fuzzy (NF) PI controller for HVDC system
Author :
Multani, Munish ; Sood, Vijay K. ; Ren, Jing
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Ontario Inst. of Technol., Oshawa, ON, Canada
fYear :
2010
fDate :
25-27 Aug. 2010
Firstpage :
1
Lastpage :
6
Abstract :
Although Fuzzy Logic (FL) controllers for HVDC systems have been previously explored, the optimization of these controllers is still part of active research. In this paper, a 4-layer Neuro-Fuzzy (NF) controller to tune the Fuzzy Rule Base is presented. FL-based PI controllers require gains values as further gains are updated around these values. The proposed controller adds intelligence to the controller as it has the capability of finding out the PI gains with changing system conditions. Gaussian and Triangular membership functions (MFs), corresponding to Radial Basis Functions (RBF) and Cerebellar Model Articulation Controller (CMAC) neural network architecture respectively, have been used to see which one offers a better performance. Results from simulations illustrate the potential of the proposed control scheme as the NF controller successfully adapts to different system conditions and is able to minimize the total current error. Furthermore, a performance comparison with a conventional PI controller is also made.
Keywords :
HVDC power transmission; PI control; fuzzy control; power system control; radial basis function networks; Gaussian membership functions; HVDC system; Triangular membership functions; adaptive neuro-fuzzy PI controller; cerebellar model articulation controller; changing system conditions; neural network architecture; radial basis functions; Artificial neural networks; Converters; Delay; Fuzzy logic; HVDC transmission; Mathematical model; Noise measurement; CMAC; HVDC Converter; Membership Function; Neuro-Fuzzy Controller; RBF;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Power and Energy Conference (EPEC), 2010 IEEE
Conference_Location :
Halifax, NS
Print_ISBN :
978-1-4244-8186-6
Type :
conf
DOI :
10.1109/EPEC.2010.5697197
Filename :
5697197
Link To Document :
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