Conjugate Unscented Transformation: Applications to Estimation and Control
Conjugate Unscented Transformation: Applications to Estimation and Control
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DOI：
10.1115/1.4037783
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发表时间：
2018-03-01
影响因子：
1.7
通讯作者：
Singh, Tarunraj
中科院分区：
文献类型：
--
作者：
Adurthi, Nagavenkat;Singla, Puneet;Singh, Tarunraj
本文提出了一种计算效率高的求多维期望积分的方法。具体地说，利用均匀密度函数和高斯函数的对称结构，构造了一些非积培养点。所提出的立方体点可以作为高斯-埃尔米特（GH）和高斯-勒让德（gaas - legendre）正交规则的有效替代，但在多维空间中积分多项式函数时，点的数量明显减少，同时保持相同的精度阶。通过在不确定性传播、非线性滤波和控制应用中的几个基准问题，证明了新开发点的优势。
This paper presents a computationally efficient approach to evaluate multidimensional expectation integrals. Specifically, certain nonproduct cubature points are constructed that exploit the symmetric structure of the Gaussian and uniform density functions. The proposed cubature points can be used as an efficient alternative to the Gauss-Hermite (GH) and Gauss-Legendre quadrature rules, but with significantly fewer number of points while maintaining the same order of accuracy when integrating polynomial functions in a multidimensional space. The advantage of the newly developed points is made evident through few benchmark problems in uncertainty propagation, nonlinear filtering, and control applications.