Optimal Control Homing of Rocket First-Stage Booster Recovery Based on Improved Genetic Algorithm with SQP

Mengping Chen, Xiaojun Xing, Yichen Han, Guozheng Fan, Yiming Guo
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Abstract

In this paper, the parafoil-rocket first stage booster system is used as the research object. Aiming at the problem of accurate fall area recovery in the first-stage booster system, a threat avoidance method of parafoil-rocket system combining genetic algorithm (GA) and sequential quadratic programming (SQP) is designed by using optimal control homing method. This method takes advantage of GA’s strong robustness and global optimization as well as SQP’s fast convergence rate and high efficiency to solve the problem of optimal control. The result of GA’s global optimization is taken as the initial value of SQP algorithm, then the local optimal solution is further obtained to solve the problem of obstacle avoidance in the complex terrain of the target landing area. The simulation results from Matlab/Simulink show that the method adopted in this paper meets the requirements of fall zone control, and compared with the path planned by the traditional GA, The path is smoother and less detour, the deviation of landing point and the error of headwind are smaller. This method has the feasibility of implementation.
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基于改进遗传算法的火箭一级助推器回收最优控制寻的研究
本文以伞翼-火箭一级助推系统为研究对象。针对第一级助推系统中精确的落区回收问题,采用最优控制寻的方法,设计了一种结合遗传算法和序列二次规划的伞翼火箭系统威胁规避方法。该方法利用遗传算法的强鲁棒性和全局寻优性以及SQP算法的快速收敛性和高效率来解决最优控制问题。将遗传算法的全局优化结果作为SQP算法的初始值,进一步求出局部最优解,解决目标着陆区复杂地形下的避障问题。Matlab/Simulink仿真结果表明,本文所采用的方法满足落区控制的要求,与传统遗传算法规划的路径相比,路径更平滑,绕路更少,着陆点偏差和逆风误差更小。该方法具有实现的可行性。
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