Title :
Design of a new kind of RBF neural network based on differential reconstruction
Author :
Zou, Huichao ; Lei, Junwei ; Pan, Changpeng
Author_Institution :
Sch. of Math. & Inf., Yantai Normal Univ.
Abstract :
A new kind of RBF neural network based on Fourier progression was studied, and the principium of its approximating unknown function was analyzed. Then it was used in a class of high order system with all unknown control function matrices. The adaptive RBF robust neural controller was designed by using back stepping method. And by adopting the trigonometric function as basis function, the input needn´t be forced to between -1 and 1, and there is no need to choose the centre of basis function. Furthermore, it is possible to make the network more stable and make the selection of simulation parameter more easy due to the introduction of differential reconstruction which increased the damp of the system. Finally, simulation study showed the effectiveness of the proposed method
Keywords :
control system synthesis; neurocontrollers; radial basis function networks; robust control; Fourier progression; RBF neural network; back stepping method; differential reconstruction; robust neural controller; unknown control function matrices; Adaptive control; Aerospace engineering; Control engineering; Control systems; Electronic mail; Gaussian processes; Information analysis; Mathematics; Neural networks; Programmable control;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614653
