改进的非线性连续-离散系统的极大似然参数估计及其应用
Improved Maximum Likelihood Estimation for Nonlinear Continuous-Discrete System and its Applications
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摘要: 对Jategaonkar等人给出的同时计及过程及观测噪声的非线性连续-离散系统的极大似 然算法从两个方面进行了改进:1)给出了计算灵敏度的最佳摄动有限差分算法,避免了普通 有限差分法计算灵敏度矩阵时需人为选择参数摄动量大小而带来的缺点;2)给出了具有快 速三角化平方根滤波的极大似然算法,提高了原算法的数值稳定性.上述改进算法经应用于 飞行器系统参数估计证明了方法的有效性.Abstract: In this paper, the maximum likelihood algorithm with process and measurement noise for nonlinear continuous-discrete system given by Jategaonkar and Plaetschke is improved in two aspects: 1) to avoid the disadvantages of sensitivities computation by common finite-difference method, in which the perturbation sizes should be selected optionally, an improved finite-difference method with best perturbations, is presented. 2) to improve the numerical stability of Jategaonkar's algorithm, maximum likelihood algorithm with fast triangular square-root decomposition filter is given. Applications to the parameter estimation of flight vehicles demonstrated the advantages of this improved algorithm.
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Key words:
- Maximum likelihood estimation /
- nonlinear system /
- sensitivity /
- square-root filter
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