Trajectory Design Optimization of Suborbital Launch Vehicle Based on Intelligent Evolutionary Algorithms

摘要：

Suborbital launch vehicle (SLV) ascent trajectory design optimization is a difficult problem due to the complexity of many constraints including path constraints and terminal constraints. Trajectory optimization problems are usually formatted as optimal control problems (OCP), which are solved in various numerical methods. In this paper, Control Vector Parameterization Method (CVPM) is used to solve the trajectory optimization problem of suborbital launch vehicle. Because ascent trajectory of suborbital launch vehicle based on program guidance, control function can be depicted by several variables. Dynamic optimal control problem is converted to static parameters optimization problem. Intelligent algorithms such as GA、 ACO、 DE and PSO were used to obtain solutions of NIP, because these algorithms have good global convergence characteristic. Finally, based on CVPM with intelligent evolutionary algorithms, optimal ascent trajectory with maximum energy per unit mass at main engine cutoff is obtained und er the constraints of dynamic pressure, normal aerodynamic acceleration, heating rate and terminal states. The result shows these algorithms are effective for trajectory optimization of SLV.

关键词： suborbital launch vehicles control vector parameterization method intelligent evolutionary algorithms trajectory optimization

作者: Wang Chenxi Li Xinguo

作者单位: College of Astronautics, Northwestern Polytechnical University, Xian 710072, China

会议类型: 国际会议

会议名称: 2010 Asia-Pacific International Symposium on Aerospace Technology(2010 亚太航空航天技术研讨会 APISAT 2010)

会议地点: 西安

会议语种:英文

页码: 686-689

在线出版日期: 2010-09-01（万方平台首次上网日期，不代表论文的发表时间）