摘要
提出将粒子群优化算法(PSO)应用于飞行器再入轨迹优化。以最小控制能量高超声速飞行器再入轨迹优化为例,对飞行器运动模型进行简化和控制量参数化,粒子群算法采用自适应权值,并充分利用飞行器再入时的运动特性来设置PSO算法初始参数,分析比较仿真步数对结果的影响。仿真结果表明提出方法的有效性和优越性。
A new method for reentry trajectory optimization is presented by using Partical Swarm Optimization（PSO）. For the minimum control energy reentry trajectory optimization for hypersonic glide vehicles, model is simplified, control variable is parameterized, adaptive weight is introuced in PSO, coefficiences are initialized by using vechicle＇s dynamic characteristics. And aslo the influence of simulation steps to the result of velocity and height is analyzed. The effectiveness and superiority of the proposed method are demonstrated by simulation results.
出处
《计算技术与自动化》
2008年第4期72-75,共4页
Computing Technology and Automation
基金
国家自然科学基金资助项目(60674105)
航天支撑基金资助项目(2008)
关键词
再入轨迹优化
粒子群优化
参数化方法
多约束
reentry trajectory optimization
partieal swarm optimization
parameterization method
Multi- constrains
