Chaotic analysis of the human brain cortical model and robust control of epileptic seizures using sliding mode control

A. Mirzaei, S. Ozgoli, A. E. Jajarm
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引用次数: 3

Abstract

In this paper, chaotic analysis of the human brain cortical model is presented. Based on these analysis, controlling of epileptic seizures, using a robust control method is considered. To this end we have utilized the mathematical model of cortical tissue activity. Chaotic behavior of this model is investigated through variations of pathological parameters. Utilization of two chaotic criteria known as entropy and largest Lyapunov exponents allowed us to monitor the chaotic behavior of the model during the reasearch. Moreover, both conniption and ending time of seizures are determined using chaotic analysis. The sliding mode method is used to design a robust controller with the purpose of controlling the seizures. The effectivness of the proposed method is shown via analysis and simulation results. Previous approches on controlling seazires did not considered robustness against the uncertainties. This problem is addressd here through designing a controller which is robust against system uncertainties. In addition to the guaranted finite time control of the seizures, consideration of the practical medical limitations for the control signal is another advantage of the proposed method.
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人脑皮质模型的混沌分析及滑模控制对癫痫发作的鲁棒控制
本文对人脑皮层模型进行了混沌分析。在此基础上,考虑采用鲁棒控制方法控制癫痫发作。为此,我们利用了皮质组织活动的数学模型。通过病理参数的变化研究了该模型的混沌行为。利用两个混沌准则,即熵和最大李雅普诺夫指数,使我们能够在研究过程中监测模型的混沌行为。此外,利用混沌分析确定了癫痫发作的开始时间和结束时间。采用滑模方法设计了鲁棒控制器,以达到控制癫痫发作的目的。分析和仿真结果表明了该方法的有效性。以前控制海潮的方法没有考虑对不确定性的鲁棒性。本文通过设计对系统不确定性具有鲁棒性的控制器来解决这一问题。除了保证对癫痫发作的有限时间控制外,考虑到控制信号的实际医学限制是所提出方法的另一个优点。
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