Resilient Integrated Guidance and Control for Long‐Range High‐Speed Aerospace Vehicles Using LSTM‐Enhanced ACHSOMC in GNSS‐Denied Environments

This study presents a next‐generation, resilient integrated guidance and control (IGC) framework for long‐range, high‐speed aerospace vehicles operating in the most contested and navigation‐degraded environments, including complete GNSS denial, high‐intensity sensor noise, and deliberate fault–injection conditions. The vehicle dynamics are modeled using an industrial‐fidelity, nonlinear six‐degree‐of‐freedom (6‐DOF) formulation that captures time‐varying mass and inertia due to fuel consumption and configuration changes, Mach‐ and flight phase–dependent aerodynamic coefficients, realistic actuator dynamics with saturation and rate limits, and inertial navigation channels affected by bias, drift, and electromagnetic interference. At the core of the design is a long short–term memory (LSTM) enhanced adaptive continuous higher‐order sliding mode controller (ACHOSMC). The LSTM module enables real‐time temporal learning to proactively compensate for navigation errors and inertial drift in the absence of GNSS, whereas the ACHOSMC law ensures robust disturbance rejection, fault accommodation, and stability preservation throughout all flight phases from initial boost to terminal approach. High‐fidelity simulations, configured to reflect rigorous industrial qualification standards, demonstrate that the proposed approach achieves a landmark improvement in precision, delivering a reduction in circular error probable (CEP) ranging from 27% to over 75% compared with established PID, SMC, and H ∞ controllers across all tested scenarios. These improvements confirm the framework′s robustness, adaptability, and suitability for advanced aerospace guidance applications in GNSS‐denied and dynamically uncertain operational domains.