Archive/Approximate Controllability of Higher-Order Hilfer Fractional Neutral Stochastic Systems Driven by Fractional Brownian Motion, Poisson Jumps, and Non-Instantaneous Impulses
Approximate Controllability of Higher-Order Hilfer Fractional Neutral Stochastic Systems Driven by Fractional Brownian Motion, Poisson Jumps, and Non-Instantaneous Impulses
A. M. Sayed Ahmed, Taha Radwan, M. Elsaid Ramadan et al.
May 16, 2026
en

Abstract

This paper addresses the existence of mild solutions and the approximate controllability of a class of higher-order Hilfer fractional semi-linear neutral stochastic differential equations with non-instantaneous impulses in Hilbert spaces. The system is driven by both fractional Brownian motion and Poisson jumps, thereby capturing long-range dependence as well as random discontinuities. By combining techniques from fractional calculus, stochastic analysis, and operator theory, we establish sufficient conditions for the existence of mild solutions. The analysis is carried out through the construction of suitable solution operator families and the application of Sadovskii’s fixed point theorem in an appropriate phase space framework. In addition, we investigate the controllability properties of the system and derive criteria ensuring approximate controllability of the underlying fractional neutral dynamics. The proposed approach relies on the structural properties of the higher-order Hilfer fractional derivative, estimates for stochastic integrals with respect to fractional Brownian motion, and compactness arguments adapted to non-instantaneous impulsive effects. The inclusion of Poisson jumps and neutral terms introduces significant analytical difficulties, which are overcome using refined resolvent operator techniques and fractional power estimates. An illustrative example is presented to demonstrate the applicability of the theoretical results. The results obtained generalize and unify several recent developments in the theory of fractional stochastic systems and provide a flexible framework for analyzing controlled dynamical models with memory, randomness, and impulsive behavior.

IPC Classification

H01

Keywords

approximatecontrollabilityhigher-orderhilferfractionalneutralstochasticsystemsdrivenbrownianmotionpoissonjumpsnon-instantaneousimpulsesfractalpaperaddressesexistencemildsolutionsclasssemi-lineardifferential
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