TY - GEN
T1 - Identification of singularly perturbed nonlinear system using recurrent high-order neural network
AU - Zheng, Dongdong
AU - Xie, Wen Fang
AU - Dai, Shu Ling
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2015/3/2
Y1 - 2015/3/2
N2 - In this paper, a new discrete time identification scheme for a singularly perturbed nonlinear system using recurrent high order multi-time scale neural network is presented. The high-order neural network (HONN) is known for its simple structure and powerful nonlinearity approximation property, which make it more suitable for modeling the singularly perturbed nonlinear systems than the multi-layer neural network [10]. An on-line identification scheme - optimal bounded ellipsoid (OBE) algorithm is developed for the recurrent high order neural network (RHONN) model. By adaptively changing the learning rate, the on-line identification scheme can achieve faster convergence compared to the other widely used learning schemes, such as backpropagation. Simulation results are presented to demonstrate the effectiveness of the proposed algorithm.
AB - In this paper, a new discrete time identification scheme for a singularly perturbed nonlinear system using recurrent high order multi-time scale neural network is presented. The high-order neural network (HONN) is known for its simple structure and powerful nonlinearity approximation property, which make it more suitable for modeling the singularly perturbed nonlinear systems than the multi-layer neural network [10]. An on-line identification scheme - optimal bounded ellipsoid (OBE) algorithm is developed for the recurrent high order neural network (RHONN) model. By adaptively changing the learning rate, the on-line identification scheme can achieve faster convergence compared to the other widely used learning schemes, such as backpropagation. Simulation results are presented to demonstrate the effectiveness of the proposed algorithm.
KW - Multi time-scale system
KW - Optimal bounded ellipsoid
KW - Recurrent high order neural network
UR - http://www.scopus.com/inward/record.url?scp=84932125542&partnerID=8YFLogxK
U2 - 10.1109/WCICA.2014.7053707
DO - 10.1109/WCICA.2014.7053707
M3 - Conference contribution
AN - SCOPUS:84932125542
T3 - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
SP - 5779
EP - 5784
BT - Proceeding of the 11th World Congress on Intelligent Control and Automation, WCICA 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 11th World Congress on Intelligent Control and Automation, WCICA 2014
Y2 - 29 June 2014 through 4 July 2014
ER -
