Design of Fuzzy Sliding Mode Controller for Heartbeat Pacemaker Based on ECG Signal Tracking
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Date
2020-11
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Addis Ababa University
Abstract
Every year, heart disease is becoming the major cause of death. Therefore, the need arises to
find advanced approaches to keep the patients safety. Implantable cardiac pacemakers are an
electronic device that can track and boost the heart rate and manage rhythm disorders.
This thesis presents nonlinear control of heartbeat model. Because of certain severe cardiac
arrhythmias display nonlinear feature which is usually correlated with unpredictable and
oscillatory behavior, a nonlinear technique is used to model heart electrical activity. Zeeman’s
heartbeat model was used to generate ECG signals. Existing model of heartbeat was analyzed
and revised by integrating the control input to add the control mechanisms as a pacemaker.
In this study, sliding mode control (SMC) is applied to heartbeat model in order to track and
generate real ECG signal. Fuzzy logic algorithm was also used with SMC to reduce chattering
happened due to high frequency oscillations around the sliding surface that will shorten the life
span of pacemaker. Therefore, a fuzzy sliding mode controller (FSMC) for cardiac pacemaker
based on ECG signal reference tracking system was designed. In addition, since the heartbeat
pacemaker is disturbed by the brain signal and sensor output delay, the robustness of the system
to disturbance, parameter variations and possible time delay on the feedback system were
analyzed.
The effectiveness of the proposed method was verified through simulation studies using Matlab/
Simulink software. The proposed control law has shown satisfactory performance in terms of
tracking ECG signal of the actual data, obtained from the MIT- Boston’s Beth Israel Hospital
(BIH), and the physioNet database by eliminating chattering compared with the use of SMC
controller. In addition, the result of root mean square error was reduced by 0.00005 % and total
harmonic distortion analyzed from FFT window was reduced by 121.35 % when FSMC was
applied to the system compared with SMC. The control strategy was also found to be robust
with respect to external disturbances, parameter variations and random feedback delay.
Therefore, control algorithm will be applied in dual sensor cardiac pacemakers for clinical use.
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Keywords
Fuzzy sliding mode control, Electrocardiogram, nonlinear heartbeat model, phase portrait analysis, time delay, disturbance