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Full-order and reduced-order optimal synchronization of neurons model with unknown parameters

Wang Xing-Yuan Ren Xiao-Li Zhang Yong-Lei

Full-order and reduced-order optimal synchronization of neurons model with unknown parameters

Wang Xing-Yuan, Ren Xiao-Li, Zhang Yong-Lei
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  • Received Date:  18 November 2010
  • Accepted Date:  01 August 2011
  • Published Online:  20 March 2012

Full-order and reduced-order optimal synchronization of neurons model with unknown parameters

    Corresponding author: Wang Xing-Yuan, wangxy@dlut.edu.cn
  • 1. School of Electronic & Information Engineering, Dalian University of Technology, Dalian 116024, China
Fund Project:  Project supported by the National Natural Science Foundation of China (Grant Nos. 61173183, 60573172, 60973152), the Superior University Doctor Subject Special Scientific Research Foundation of China (Grant No. 20070141014), and the Natural Science Foundation of Liaoning Province, China (Grant No. 20082165).

Abstract: Based on Lyapunov stability theory, optimal control principle and step design methodology, nonlinear feedback controller and optimal controller are designed, in which the nonlinear feedback controller makes the trajectory error between two neuron systems tend to zero, and the optimal controller makes the spent energy meet minimum, which is spent in the process of synchronizing. In this paper, the uncertain cable model is taken as an example to illustrate the full-order optimal synchronization of two neurons. The uncertain cable model and the uncertain Hindmarsh-Rose (HR) model are taken to illustrate the reduced-order optimal synchronization of two neurons. In addition, the unknown parameters are identified successfully. Numerical Simulation results show the effectiveness of the strategy further.

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