Integrated optimization of de-spin actuator design and operating parameters for tail-controlled flight vehicle

Abstract

Achieving high-precision guidance for high-spinning flight vehicles necessitates effective de-spin actuator design that simultaneously preserves flight stability. This study presents an innovative integrated optimization framework for Tail-controlled Flight Vehicles (TFV) with a dual-spin structure. We first propose a novel de-spin actuator design for the Aft Control Kit (ACK) to facilitate a stable low-spin environment while maintaining the forebody's high-spin stability. Crucially, a Phy-sense Neural Network (PSNN) is introduced for high-fidelity aerodynamic coefficient prediction, demonstrating a significant 58% error reduction compared to conventional Conv1D models by integrating fundamental fluid dynamics principles. Furthermore, we develop a decoupled integrated optimization strategy based on quantitative sensitivity analysis. This strategy, combined with a seven-degree-of-freedom (7-DoF) ballistic model, systematically optimizes the de-spin fin's configuration and operating parameters. The comprehensive framework significantly improves both overall flight performance and de-spin effectiveness. Simulation and experimental results rigorously validate the proposed design's capabilities, offering valuable methodological insights for the advanced design and optimization of future high-spinning vehicles.