Published August 2017 | Version v1
Journal article

Robust stabilization control of bifurcations in Hodgkin-Huxley model with aid of unscented Kalman filter

  • 1. Tianjin Key Laboratory of Information Sensing & Intelligent Control, School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222 (China)
  • 2. School of Information Technology and Engineering, Tianjin University of Technology and Education, Tianjin 300222 (China)
  • 3. School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

Description

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.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.chaos.2017.04.045

Additional details

Identifiers

DOI
10.1016/j.chaos.2017.04.045;
PII
S0960-0779(17)30180-7;

Publishing Information

Journal Title
Chaos, Solitons and Fractals
Journal Volume
101
Journal Page Range
p. 92-99
ISSN
0960-0779

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
49087707
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
BIFURCATION; DISEASES; FILTERS; LYAPUNOV METHOD; SIMULATION; STABILIZATION
Descriptors DEC
CALCULATION METHODS

Optional Information

Copyright
Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.