Adaptive Higher Order Continuous Sliding Mode Integrated Guidance and Control With Neural Disturbance Compensation for Intercepting Maneuvering Targets

Existing integrated guidance and control (IGC) schemes often face a trade‐off between chattering suppression and rapid adaptability, particularly when relying on single‐parameter tuning or discontinuous switching laws. To bridge this gap, this paper proposes a novel adaptive continuous higher order sliding mode controller (ACHOSMC) designed for autonomous aerial systems operating in highly contested, GPS‐denied environments. The primary innovation lies in the integration of a fourth‐order continuous sliding manifold with a dual‐parameter neural network (NN) adaptation mechanism. Unlike conventional adaptive approaches that tune a single gain, the proposed architecture utilizes two lightweight NNs to simultaneously optimize both the integral and shaping gains in real‐time. This dual‐adaptation strategy enables the controller to aggressively reject compound disturbances—including wind gusts, sensor noise, and aerodynamic uncertainties—while maintaining a smooth, chattering‐free control signal. Lyapunov analysis confirms global ultimate boundedness, and comparative simulations in a fully coupled 3D engagement scenario demonstrate the method′s superiority. Quantitative results reveal that ACHOSMC reduces time‐to‐intercept by 89.7% relative to PID and 48.0% relative to nonadaptive CHOSMC, whereas increasing terminal intercept altitude by over 619%. These findings validate ACHOSMC as a robust, combat‐ready solution that merges the precision of higher order dynamics with the flexibility of online neural learning.