基于ALPSO算法的低轨卫星小推力离轨最优控制方法

低轨卫星在到寿后,需要在一定时间内离轨,而轨道高度高于800 km的卫星难以在自然条件下离轨。为了使卫星在规定时间内离轨,提出一种基于增广拉格朗日粒子群优化(augmented Lagrangian particle swarm optimization, ALPSO)算法的低轨卫星小推力离轨最优控制算法。首先依据小推力的特点列出摄动方程,并利用哈密尔顿方程求出带协状态参数的最优控制率。而后分别阐述了粒子群算法和增广拉格朗日方法,并据此得出了算法流程。最后与遗传算法的优化结果进行对比。结果表明, ALPSO算法迭代次数较少,收敛精度较高,降低轨道高度的第一种处置轨道适用于轨道高度821 km的卫星离轨,离轨时间为857天。该算法可用于低轨卫星小推力离轨问题的求解。

Optimal control method for low thrust deorbit of the low earth orbit satellite based on ALPSO algorithm

The low earth orbit satellite needs to deorbit within a certain period of time after reaching their lifetime, while satellite with orbit height above 800 km is difficult to deorbit under natural conditions. In order to make the satellite deorbit within a specified time, an optimal control algorithm for low thrust deorbit of the low earth orbit satellite based on the augmented Lagrangian particle swarm optimization (ALPSO) algorithm is proposed. Firstly, the perturbation equation is listed according to the characteristics of low thrust, and the Hamilton equation is used to acquire the optimal control rate with co-state parameters. Then, the particle swarm algorithm and the augmented Lagrangian method are expounded respectively, and the algorithm flow is obtained accordingly. Finally, it is compared with the optimization results of the genetic algorithm. The results show that the ALPSO algorithm has fewer iterations and higher convergence accuracy. The first disposal orbit with reduced orbit altitude is suitable for satellite deorbit with an orbit altitude of 821 km, and the deorbit time is 857 days. The algorithm can be applied to solve the low thrust deorbit problem of the low earth orbit satellite.