| 大气层内固体火箭多约束鲁棒三维能量管理制导 |
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| 引用本文： | 刘飞,王松艳,杨明,晁涛.大气层内固体火箭多约束鲁棒三维能量管理制导[J].宇航学报,2022,43(12):1652-1664. |
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| 作者姓名： | 刘飞 王松艳 杨明 晁涛 |
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| 作者单位： | 哈尔滨工业大学航天学院控制与仿真中心，哈尔滨 150001 |
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| 基金项目： | 国家自然科学基金（61627810, 61790562,61403096） |
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| 摘 要： | 针对固体运载火箭大范围精确调节终端约束的要求，提出一种新型的大气层内鲁棒三维能量管理制导方法，通过在线规划侧向速度能力曲线消耗剩余发动机能量。将终端约束表示为关于攻角和速度能力曲线参数的方程组，将闭环制导问题转化为方程组的求解。针对飞行过程中的动压、过载，以及控制变化率等过程约束，构造了攻角和速度能力曲线的可行边界。针对气动系数和发动机参数的不确定性，采用容积卡尔曼滤波器对不确定性进行辨识。仿真结果表明，与模型预测静态规划算法和改进粒子群算法相比，本算法的终端速度调节范围、鲁棒性以及计算效率大幅度提高。
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| 关 键 词： | 固体火箭 上升段制导 能量管理 多约束 不确定性 |
| 收稿时间： | 2022-04-08 |
Multi constraint Robust Three dimensional Energy Management Guidance for Solid propellant Launch Vehicles during Endo atmospheric Flight |
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| LIU Fei,WANG Songyan,YANG Ming,CHAO Tao.Multi constraint Robust Three dimensional Energy Management Guidance for Solid propellant Launch Vehicles during Endo atmospheric Flight[J].Journal of Astronautics,2022,43(12):1652-1664. |
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| Authors: | LIU Fei WANG Songyan YANG Ming CHAO Tao |
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| Affiliation: | Control and Simulation Center, School of Astronautics, Harbin Institute of Technology, Harbin 150001, China |
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| Abstract: | In order to accurately adjust terminal constraints in a large range for solid propellant launch vehicles, a novel robust three dimensional energy management guidance method in endo atmosphere is proposed. The remaining engine energy is consumed by on line programming of the lateral velocity capability curve. The terminal constraints are expressed as equations about angle of attack and velocity capability curve parameters, and the closed loop guidance problem is transformed into the solution of the equations. Aiming at path constraints such as dynamic pressure, overload and control rate of change during flight, the feasible boundary of the angle of attack and velocity capability curve is constructed. In view of the aerodynamic coefficients and engine parameter uncertainties, the cubature Kalman filters (CKF) is used to identify the uncertainties. The simulation results show that compared with the model predictive static programming algorithm and the improved particle swarm optimization algorithm, the proposed algorithm greatly improves the adjustment range of the terminal velocity, robustness and computational efficiency. |
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| Keywords: | Solid propellant launch vehicle Ascent guidance Energy management Multiple constraints Uncertainty |
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