论文标题

甚至订购明确的符号几何算法,用于通过对角帕德近似和Cayley Transformation和Cayley Transform在指导导航和控制中求解四算法

Even Order Explicit Symplectic Geometric Algorithms for Solving Quaternions in Guidance Navigation and Control via Diagonal Padé Approximation and Cayley Transform

论文作者

Zhang, Hong-Yan, Liu, Fei, Zhou, Yu, Liang, Man

论文摘要

四元运动运动差分方程(QKDE)在导航,控制和指导系统中起关键作用。尽管可以使用此问题的显式符号几何算法(ESGA),但缺乏统一的方法来构建具有可配置订单参数的高阶符号差异方案,并且应仔细处理分数间隔抽样问题。我们提出了均匀的显式符号几何算法,以通过对角线帕德近似通过四步策略来解决QKDE。首先,证明了Padé-cayley引理并用来简化具有无限象征结构的线性汉密尔顿系统的象征性帕德近似。其次,提出了平行和替代迭代方法,以均匀的订单准确性构建符合性差异方案。第三,单步过渡矩阵的符合性,正交性和可逆性被严格证明。最后,显式符号几何算法是针对线性时变和线性时间变化的QKDE设计的。解决QKDE的最大绝对错误是$ \ MATHCAL {O}(((T_F-T_0)τ^{2 \ ell})$,其中$τ$是时间步骤,$ \ ell $是订单参数,$ [t_0,t_0,t_f] $是时间范围。线性时间复杂性和计算的恒定空间复杂性以及简单的算法结构表明,我们的算法适用于航空,宇航学,机器人技术等的实时应用。通过数学分析和数值模拟来验证和验证所提出的算法的性能。

Quaternion kinematical differential equation (QKDE) plays a key role in navigation, control and guidance systems. Although explicit symplectic geometric algorithms (ESGA) for this problem are available, there is a lack of a unified way for constructing high order symplectic difference schemes with configurable order parameter and the fractional interval sampling problem should be treated carefully. We present even order explicit symplectic geometric algorithms to solve the QKDE with diagonal Padé approximation via a four-step strategy. Firstly, the Padé-Cayley lemma is proved and used to simplify the symplectic Padé approximation for the linear Hamiltonian system with infinitesimal symplectic structure. Secondly, both parallel and alternative iterative methods are proposed to construct the symplectic difference schemes with even order accuracy. Thirdly, the symplecity, orthogonality and invertibility of the single-step transition matrices are proved rigorously. Finally, the explicit symplectic geometric algorithms are designed for both the linear time-invariant and linear time-varying QKDE. The maximum absolute error for solving the QKDE is $\mathcal{O}((t_f-t_0)τ^{2\ell})$ where $τ$ is the time step, $\ell$ is the order parameter and $[t_0,t_f]$ is the time span. The linear time complexity and constant space complexity of computation as well as the simple algorithmic structure show that our algorithms are appropriate for real-time applications in aeronautics, astronautics, robotics and so on. The performance of the proposed algorithms are verified and validated by mathematical analysis and numerical simulation.

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