A quantum-inspired neural fuzzy sliding mode control framework for fractional-order modeling of intraocular pressure regulation and optic nerve damage in glaucoma
David Amilo
Abstract
Glaucoma, a progressive neurodegenerative ocular disease, is primarily driven by elevated intraocular pressure (IOP), which results in optic nerve damage and irreversible vision loss. This study introduces a novel fractional-order mathematical model to capture the intricate dynamics of aqueous humor production, drainage, and the associated deterioration of the optic nerve in glaucoma. Building on this framework, this work proposes a Quantum-Inspired Neural Fuzzy Sliding Mode Control (QINF-SMC) framework, designed to address the nonlinear and time-varying nature of IOP regulation. The model highlights that persistent elevation in IOP leads to continuous optic nerve damage and disease progression, while impaired outflow resistance exacerbates glaucoma. Conversely, stable aqueous humor dynamics maintain normal IOP, preventing disease advancement. The proposed QINF-SMC framework integrates fractional-order calculus, fuzzy logic, and quantum-inspired optimization to achieve precise and adaptive control of IOP, mitigate optic nerve damage, and optimize aqueous humor dynamics. The framework achieves near-perfect 97.9% convergence, with excellent control stability and tightly regulated parameters, combining fast global optimization with precise refinement through advanced fractional-order dynamics. This approach offers a robust and innovative strategy for managing glaucoma, with potential implications for improving therapeutic outcomes and preserving vision.