考虑姿态平滑性优化的动力着陆双推力切换解析制导算法
Dual-Thrust Switching Analytical Guidance Algorithm for Powered Landing with Attitude Smoothness Optimization
AI总结：
本文针对可重复使用火箭动力着陆现有数值制导方法的局限，提出一种优化姿态平滑性、支持双推力模式切换的解析制导算法，该算法计算效率高、实时性强，可在复杂条件下实现高精度着陆，具备良好工程应用前景。
AI中文摘要：
传统可重复使用火箭动力着陆的数值制导方法通常受限于高计算复杂度和不足的实时性能。此外，对姿态平滑性考虑不足常导致控制命令出现严重波动；同时，现有大多数方法针对单推力场景设计，无法满足多发动机推力切换的制导需求。为缓解这些局限，本文提出一种优化姿态平滑性、支持双推力模式切换的解析制导方法。首先，构建对应的最优控制问题，并从理论上证明最优姿态命令呈现简洁的分段三次函数形式，这将复杂的轨迹优化转化为参数化解析优化问题，大幅提升计算效率。进一步，设计三相制导框架以自适应确定制导激活点和推力切换点；结合气动修正策略时，该框架可增强方法在复杂飞行环境，尤其是高升阻比条件下的适应性。仿真结果表明，所提方法生成的姿态命令曲线与理论最优解高度吻合，且计算时间极短，证实其具备在线实时实现的强大潜力。即使在严格条件（如推力调节范围有限、高升阻比、参数偏差）下，该方法仍能持续实现高精度着陆，展现出良好的工程应用前景。
英文摘要：
Traditional numerical guidance methods for powered landing of reusable rockets are typically constrained by high computational complexity and inadequate real-time performance. Moreover, insufficient consideration of attitude smoothness often induces severe fluctuations in control commands; meanwhile, most existing approaches are tailored for single-thrust scenarios, failing to accommodate the guidance requirements of multi-engine thrust switching. To mitigate these limitations, this paper proposes an analytical guidance method optimized for attitude smoothness, which supports dual-thrust-mode switching. First, a corresponding optimal control problem is formulated, and it is theoretically proven that the optimal attitude command takes a concise piecewise cubic function form. This transforms complex trajectory optimization into a parametric analytical optimization problem, yielding a substantial improvement in computational efficiency. Further, a three-phase guidance framework is designed to enable adaptive determination of the guidance activation point and thrust switching point; when integrated with an aerodynamic correction strategy, this framework enhances the method's adaptability in complex flight environments particularly under high lift-to-drag ratio conditions. Simulation results demonstrate that the attitude command profile generated by the proposed method aligns closely with the theoretical optimal solution, with an ultra-short computation time, confirming its strong potential for online real-time implementation. Even under stringent conditions (e.g., limited thrust adjustment range, high lift-to-drag ratios, and parameter deviations), the method consistently achieves high-precision landing, showcasing promising prospects for engineering applications.
