Title :
Study on Sliding Mode Control with RBF Network for DSTATCOM
Author :
Xu, Yanqing ; Ma, Caoyuan ; Yang, Longyue ; Gong, Zheng ; Pu, Hailin ; Zhang, Zhen
Author_Institution :
China Univ. of Min. & Technol., Xuzhou, China
Abstract :
For the problems of parameters disturbance, nonlinear and uncertainty of distribution static compensator (DSTATCOM), this paper studies on sliding mode control based on radial basis function (RBF) network. The fast tracking of DSTATCOM reactive current is achieved by using of RBF neural networks and equivalent sliding mode control. The method has a strong adaptability and robustness for load disturbances and system parameters change, and integrates the advantages of neural network and sliding mode control, so it is an ideal intelligent control strategy .The MATLAB simulation results show that the controller has good dynamic and static quality, and provides an effective way for improving the performance of DSTATCOM.
Keywords :
neurocontrollers; radial basis function networks; static VAr compensators; variable structure systems; DSTATCOM reactive current; MATLAB simulation; RBF neural networks; distribution static compensator; intelligent control strategy; load disturbances; parameters disturbance; radial basis function network; sliding mode control; system parameters change; Capacitance; Equations; Mathematical model; Radial basis function networks; Robustness; Sliding mode control;
Conference_Titel :
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location :
Henan
Print_ISBN :
978-1-4244-7159-1
DOI :
10.1109/ICEEE.2010.5661056