TY - JOUR
T1 - Robust stabilization control of bifurcations in Hodgkin-Huxley model with aid of unscented Kalman filter
AU - Che, Yanqiu
AU - Liu, Bei
AU - Li, Huiyan
AU - Lu, Meili
AU - Wang, Jiang
AU - Wei, Xile
N1 - Funding Information:
This work is supported by The National Natural Science Foundation of China (Grants No. 61501330, No. 61374182, No. 61401312, No. 61471265 and No. 61372010) and The Natural Science Foundation of Tianjin, China (Grant No. 15JCYBJC1900010). We would also acknowledge the support of Tianjin University of Technology and Education (Grants No. RC14-09, No. RC14-48, and No. RC14-49). We are grateful to the editor and reviewers for their valuable comments and suggestions.
Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2017/8
Y1 - 2017/8
N2 - A stabilization control method combined with the unscented Kalman filter (UKF) is proposed to control bifurcations in Hodgkin–Huxley neuronal system which are highly related to the occurrence of many dynamical diseases. In neuronal system, usually only the membrane potential can be measured with noise, thus the existing bifurcation controllers, which require exact information of all system states, are impractical. In our method, the system states used to construct the bifurcation controller are estimated by the UKF from partial noisy measurements. The stability of the controlled closed loop system is guaranteed by Lyapunov stability theory. Simulation results demonstrate the effectiveness of the proposed method. The designed controller may have potential applications in the therapy of dynamical diseases.
AB - A stabilization control method combined with the unscented Kalman filter (UKF) is proposed to control bifurcations in Hodgkin–Huxley neuronal system which are highly related to the occurrence of many dynamical diseases. In neuronal system, usually only the membrane potential can be measured with noise, thus the existing bifurcation controllers, which require exact information of all system states, are impractical. In our method, the system states used to construct the bifurcation controller are estimated by the UKF from partial noisy measurements. The stability of the controlled closed loop system is guaranteed by Lyapunov stability theory. Simulation results demonstrate the effectiveness of the proposed method. The designed controller may have potential applications in the therapy of dynamical diseases.
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U2 - 10.1016/j.chaos.2017.04.045
DO - 10.1016/j.chaos.2017.04.045
M3 - Article
AN - SCOPUS:85019900935
SN - 0960-0779
VL - 101
SP - 92
EP - 99
JO - Chaos, Solitons and Fractals
JF - Chaos, Solitons and Fractals
ER -