TY - GEN
T1 - Neural network H-infinity synchronization control for time delay chaotic neuronal systems
AU - Che, Yanqiu
AU - Liu, Bei
AU - Li, Huiyan
AU - Qin, Yingmei
AU - Han, Chunxiao
N1 - Funding Information:
This work was supported by The National Natural Science Foundation of China (Grants Nos. 61374182, 61401312), The Natural Science Foundation of Tianjin, China (Grants Nos. 15JCYBJC19000, 13JCQNJC03700) and Open Project of The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences under Grant 20130101. We would also acknowledge the support of Tianjin University of Technology and Education (Grants Nos. RC14-09, RC14-49, RC14-59)
PY - 2016/8/3
Y1 - 2016/8/3
N2 - This paper proposes a hybrid synchronization scheme for chaotic systems with input time delay and uncertainty. In the proposed framework, radial basis function (RBF) neural networks (NNs) are constructed to approximate the unknown smooth nonlinear functions of the synchronization error system. The time delay part is dealt with an adaptive controller and the effect of approximate errors, uncertainties and disturbances are reduced to a H∞ norm constraint. By Lyapunov stability theorem, the closed-loop of the controlled synchronization error system is proved to be stable around zero. Thus the synchronization of chaotic systems is obtained. A simulation example with Hindmarsh-Rose neuronal systems is presented to demonstrate the validity of the proposed control method.
AB - This paper proposes a hybrid synchronization scheme for chaotic systems with input time delay and uncertainty. In the proposed framework, radial basis function (RBF) neural networks (NNs) are constructed to approximate the unknown smooth nonlinear functions of the synchronization error system. The time delay part is dealt with an adaptive controller and the effect of approximate errors, uncertainties and disturbances are reduced to a H∞ norm constraint. By Lyapunov stability theorem, the closed-loop of the controlled synchronization error system is proved to be stable around zero. Thus the synchronization of chaotic systems is obtained. A simulation example with Hindmarsh-Rose neuronal systems is presented to demonstrate the validity of the proposed control method.
UR - http://www.scopus.com/inward/record.url?scp=84983775598&partnerID=8YFLogxK
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U2 - 10.1109/CCDC.2016.7531994
DO - 10.1109/CCDC.2016.7531994
M3 - Conference contribution
AN - SCOPUS:84983775598
T3 - Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016
SP - 5575
EP - 5580
BT - Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th Chinese Control and Decision Conference, CCDC 2016
Y2 - 28 May 2016 through 30 May 2016
ER -