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Fractional order PID system for suppressing epileptic activities

Lookup NU author(s): Lijuan Xia, Professor Andrew Jackson, Dr Graeme Chester, Dr Patrick Degenaar

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Abstract

© 2018 IEEE. Epilepsy is a dynamic disorder of the brain at the system level which is due to abnormal activity of the brain cells. A closed-loop control system is designed in this work to detect the epileptic seizures and hence to suppress it through stimulating the brain cells. Proportional-Integral-Derivative (PID) is the most extensively used closed loop controller because of its simple implementation and robust performance. Although some efforts have been done to use PID controller to suppress the abnormal brain activities, the previously proposed systems were limited for specific cases or model parameters due to the stability constraints. This work is proposing to use the fractional order PID which is the generalization of the traditional PID system to suppress the epileptic seizures. By using the fractional PID, different stability domains are created based on the fractional orders and hence more degree of freedom for the system parameters. In this work, the Neural Mass Model (NMM) is used as a test platform for the controller for suppressing the brain activity. A graphical technique for stability contours is illustrated in this work to make the parameters determination easy for different stability conditions. MATLAB simulations are conducted to verify the controller performance, and the simulation results show the ability of the controller to suppress the focal epilepsy seizures at different scenarios.


Publication metadata

Author(s): Soltan A, Xia L, Jackson A, Chester G, Degenaar P

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of 4th IEEE International Conference on Applied System Innovation 2018, ICASI 2018

Year of Conference: 2018

Pages: 338-341

Online publication date: 25/06/2018

Acceptance date: 02/04/2018

Publisher: Institute of Electrical and Electronics Engineers Inc.

URL: https://doi.org/10.1109/ICASI.2018.8394603

DOI: 10.1109/ICASI.2018.8394603

Library holdings: Search Newcastle University Library for this item

ISBN: 9781538643426


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