An Adaptive Barrier Function Terminal Sliding Mode Controller for Partial Seizure Disease Based on the Pinsky–Rinzel Mathematical Model

Zahra Mokhtare, Mai The Vu, Saleh Mobayen () and Thaned Rojsiraphisal ()
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Zahra Mokhtare: Department of Electrical Engineering, University of Zanjan, Zanjan 45195-313, Iran
Mai The Vu: School of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea
Saleh Mobayen: Department of Electrical Engineering, University of Zanjan, Zanjan 45195-313, Iran
Thaned Rojsiraphisal: Advanced Research Center for Computational Simulation, Department of Mathematics, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand

Mathematics, 2022, vol. 10, issue 16, 1-13

Abstract: This paper proposes an adaptive barrier function terminal sliding mode control method for partial seizure based on the Pinsky–Rinzel model. A terminal sliding mode control technique is designed to achieve the convergence of trajectories to the desired value in a finite time, while an adaptive barrier function is used to ensure that the outputs, which are independent of the disturbance boundary, converge to the predetermined zero location. The performance of the proposed approach is checked for the nonlinear two-compartmental Pinsky–Rinzel pyramidal neuron model. The obtained method of the finite time stability, in the presence of uncertainty and disturbance, is proven by the Lyapunov theory. The simulation results confirm the effectiveness of the proposed control scheme. Finite time convergence, robustness, chattering-free dynamics and near-zero error are the advantages of the proposed technique.

Keywords: Pinsky–Rinzel model; terminal sliding mode control; partial seizure; adaptive barrier function; uncertainty (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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