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Spacecraft Attitude Control using Path Integral Method via Riemann Manifold Hamiltonian Monte Carlo

机译:利用路径积分方法通过黎曼流形哈密顿量蒙特卡罗控制航天器的姿态

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The separation principle for control and estimation is the traditional method for stochastic optimal control of linear systems. However, such an approach does not hold true as systems become increasingly nonlinear. This paper presents a new method for control through estimation based on the Path Integral (PI) formulation and the Riemann Manifold Hamiltonian Monte Carlo (RMHMC) method. The approach uses the path integral method to formulate the control problem as an estimation problem and adds the estimation of the model parameters to the problem. Then, a solution is found by solving the estimation problem by Riemann Manifold Hamiltonian Monte Carlo (RMHMC) sampling which includes a solution for the control parameters. By solving the nonlinear control and estimation problem using the path integral method via RMHMC, no open algorithmic tuning parameters other than exploration noise are required and the control solution has numerically robust performance to high dimensionality in the system control input. The methodology is specifically applied to the spacecraft attitude control problem, though it should be noted that such an approach is generalizable. Simulation results are presented which demonstrate good performance when utilizing the PI via RMHMC method.
机译:控制和估计的分离原理是线性系统随机最优控制的传统方法。但是,随着系统变得越来越非线性,这种方法并不适用。本文提出了一种基于路径积分(PI)公式和黎曼流形汉密尔顿蒙特卡洛(RMHMC)方法的估计控制新方法。该方法使用路径积分法将控制问题表述为估计问题,并将模型参数的估计添加到该问题。然后,通过用黎曼流形汉密尔顿蒙特卡洛(RMHMC)采样解决估计问题来找到解决方案,其中包括控制参数的解决方案。通过使用RMHMC的路径积分方法解决非线性控制和估计问题,除探索噪声外,不需要任何开放的算法调整参数,并且该控制解决方案在系统控制输入中具有对高维的数值鲁棒性能。该方法特别适用于航天器姿态控制问题,但应注意,这种方法是可推广的。仿真结果表明,当通过RMHMC方法利用PI时,表现出良好的性能。

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