Abstract
Multiple sclerosis is an inflammatory autoimmune disease which involves brain. The myelin and axons of the central nervous system (CNS) are attacked by the penetrative immune cells; this action contributes to some irreversible physical disabilities. MS is a heterogeneous disease; therefore, extracting a perfect model including all the subtypes of the illness is very challenging. Here, a recently proposed state space model of MS is considered and by taking a stimulus signal as the control input, a fuzzy sliding mode controller is designed for a more realistic condition, that is, two principal coefficients of the mode are uncertain. The simulation results demonstrate appropriate performance of the proposed controller.
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Kohanpour, E., Taghvaei, S., Vatankhah, R., Eghtesad, M. (2020). Robust Fuzzy Sliding Mode Controller Design for a Multiple Sclerosis Model. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A., Sari, I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, vol 1029. Springer, Cham. https://doi.org/10.1007/978-3-030-23756-1_157
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DOI: https://doi.org/10.1007/978-3-030-23756-1_157
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