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A nearly optimal control for spacecraft rendezvous with constrained controls

机译:受约束控制的航天器交会的几乎最佳控制

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摘要

A neural network Hamilton-Jacobi-Bellman (HJB) approach is introduced to deal with the spacecraft rendezvous problem with target spacecraft in arbitrary elliptical orbit. The Lawden equations are utilized to describe the relative motion of two spacecrafts. A generalized non-quadratic functional is introduced to describe constrained control. An approximate solution to the value function of the HJB equation corresponding to constrained controls is obtained by solving for a sequence of cost functions satisfying a sequence of Lyapunov equations. An inverse optimal controller is introduced to design the initial stabilizing admissible control for successive approximation. Furthermore, an optimal control law is obtained to stabilize the closed-loop system under constrained controls, and the spacecraft rendezvous mission can be accomplished with the nearly optimal controller. In comparison with the existing quadratic-regulation-based approaches used to deal with the rendezvous problem, which requires the value function of the nonlinear differential equations, the optimization factor and constrained control are taken into consideration simultaneously, and an approximate optimal constrained state feedback controller has been tuned a priori off-line. Stability analysis as well as simulation results are provided to illustrate the effectiveness of the presented approach.
机译:引入了神经网络哈密顿-雅各比-贝尔曼(HJB)方法来处理目标椭圆轨道在任意椭圆轨道上的航天器交会问题。劳登方程被用来描述两个航天器的相对运动。引入广义非二次函数来描述约束控制。通过求解满足一系列Lyapunov方程的成本函数序列,可以获得与约束控制相对应的HJB方程的值函数的近似解。引入了逆最优控制器,以设计用于逐次逼近的初始稳定允许控制。此外,获得了最优控制定律以稳定受约束控制下的闭环系统,并且航天器的交会任务可以用几乎最优的控制器来完成。与用于解决会合问题的基于二次调节的现有方法相比,该方法需要非线性微分方程的值函数,同时考虑了优化因子和约束控制,并且采用了近似最优约束状态反馈控制器已先验离线优化。提供稳定性分析以及仿真结果来说明所提出方法的有效性。

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