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

机译:航天器姿态控制通过riemann多方的方法使用路径积分法汉密尔顿蒙特卡罗

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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佳控制的传统方法。然而,随着系统变得越来越多的非线性,这种方法并没有保持真实。本文介绍了基于路径积分(PI)制剂的估计来控制的新方法,以及瑞曼歧管Hamiltonian Monte Carlo(RMHMC)方法。该方法使用路径积分方法将控制问题作为估计问题,并将模型参数的估计添加到问题。然后,通过求解Riemann歧管Hamiltonian Monte Carlo(RMHMC)采样的估计问题来发现一种解决方案,其包括用于控制参数的解决方案。通过通过RMHMC求解路径积分方法的非线性控制和估计问题,不需要探索噪声以外的开放算法调谐参数,并且控制解决方案对系统控制输入中的高维度具有数值鲁棒性能。该方法专门应用于航天器姿态控制问题,尽管应该注意的是,这种方法是更广泛的。提出了仿真结果,其通过RMHMC方法利用PI时表现出良好的性能。

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