STABILITY ANALYSIS AND ADAPTIVE SLIDING MODE CONTROL OF A STOCHASTIC NIPAH SEIR MODEL

Dewi Dian Suhika, Nela Wiadnyana Rizka

Abstract


Nipah virus is a zoonotic pathogen capable of human-to-human transmission, with transmission dynamics influenced by uncertainty in the infection process. This study aims to analyze stability and design an adaptive sliding mode control for a SEIR (susceptible, exposed, infectious, and removed) model to suppress infection spread under transmission uncertainty. The stability of the controlled system is analyzed using the Lyapunov method, while controller performance is evaluated through deterministic and stochastic simulations. The stability analysis shows that, under the stated conditions, the sliding surface converges asymptotically to zero in the deterministic case, whereas in the stochastic case it is practically bounded in the mean-square sense. Deterministic simulation results show that the peak proportion of infectious individuals decreases from 0.3267 on day 43.6 to 0.0481 on day 25 after control is applied. Stochastic simulations with 200 Monte Carlo realizations show a consistent reduction, with the mean peak decreasing to 0.0477. These results indicate that the adaptive sliding mode control can suppress infection dynamics and maintain control performance under the transmission uncertainty considered.

Keywords


Stochastic Model; Adaptive Sliding Mode Control; Lyapunov; Nipah Virus

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References


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DOI: https://doi.org/10.15548/mej.v10i2.14988

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