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《International Journal of Automation and Computing》 2017年02期
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An Adaptive Regulation Problem and Its Application

Yuan Jiang  Ji-Yang Dai  
【摘要】:This paper studies an adaptive regulation problem for the modified Fitz Hugh-Nagumo neuron model under external electrical stimulation. We first present the solution of the global robust output regulation problem for output feedback system with an uncertain exosystem which models the external electrical stimulation with unknown frequency and amplitude. Then, we show that the robust control problem for the modified Fitz Hugh-Nagumo neuron model can be formulated as the global robust output regulation problem and the solvability conditions for the output regulation problem for the modified Fitz Hugh-Nagumo neuron model are all satisfied. Then, we apply the obtained output regulation result to constructing an output feedback control law for the modified Fitz Hugh-Nagumo neuron model to achieve global stability of the closed-loop system in the presence of uncertain parameters and external stimulus. An example is given to show that the proposed algorithm can completely reject the external electrical stimulation.
【作者单位】Key
【关键词】Control theory Lyapunov methods internal model principle modified Fitz Hugh-Nagumo model
【基金】:supported by National Natural Science Foundation of China(No.61164015) Natural Science Foundation of Jiangxi Province(No.20142BAB207021) Foundation of Jiangxi Educational Committee(No.GJJ12437) Open Fund of Key Laboratory of Image Processing and Pattern Recognition of Jiangxi Province(Nanchang Hangkong University)(No.TX201404003) Scientific Research Foundation for the Doctors of Nanchang Hangkong University(No.EA201104184)
【分类号】:O231
【正文快照】:
1 IntroductionThe modified Fitz Hugh-Nagumo equations are a set of 3coupled differential equations which exhibit the qualitativebehavior observed in neurons,viz quiescence,excitabilityand periodicity[1].The dynamic equations for the controlledmodified Fi

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