引用本文: | 沈强,刘洁瑜,赵乾,王琪.非线性系统中心差分集员估计方法[J].控制理论与应用,2019,36(8):1239~1249.[点击复制] |
SHEN Qiang,LIU Jie-yu,ZHAO Qian,WANG Qi.Central difference set-membership filter for nonlinear system[J].Control Theory and Technology,2019,36(8):1239~1249.[点击复制] |
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非线性系统中心差分集员估计方法 |
Central difference set-membership filter for nonlinear system |
摘要点击 3094 全文点击 1184 投稿时间:2018-05-19 修订日期:2018-09-30 |
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DOI编号 10.7641/CTA.2018.80369 |
2019,36(8):1239-1249 |
中文关键词 非线性系统 集员估计 状态估计 参数估计 有界噪声 计算复杂度 中心差分 |
英文关键词 nonlinear system set membership estimation state estimation parameter estimation bounded noise computational complexity central difference |
基金项目 国家自然科学基金 |
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中文摘要 |
用于非线性椭球估计的扩展集员算法在实际应用中存在着实现性差、边界估计相对保守等缺陷. 本文提出了一种用于非线性系统状态估计的中心差分集员估计方法, 以改善传统非线性集员滤波算法的估计性能. 为克服泰勒展开的固有缺陷, 采用低阶多维Stirling内插多项式代替泰勒展开实现非线性模型的线性化处理; 利用半定规划方法对线性化误差进行外包定界并将其融入过程噪声和量测噪声中, 以降低误差定界的保守性; 量测更新中, 为提高算法的实时性, 将量测椭球松弛为多个带的交, 依次参与状态椭球的更新, 从而实现状态定界椭球的次优估计; 同时, 对椭球-带交集迭代过程中椭球中心到超平面的归一化距离的计算方法进行了改进, 使当前时刻每次迭代的椭球均参与计算并选取最优值, 以减小累计误差. 仿真结果表明了本文所提出算法的有效性和改进性能. |
英文摘要 |
The extended set-membership filter for nonlinear ellipsoidal estimation has some shortcomings such as poor implementation and relatively conservative estimated boundary. In this paper, a central difference set-membership filter for nonlinear system state estimation is proposed to improve the estimation performance of traditional nonlinear set-membership filter. To overcome the inherent defect of Taylor’s formula, a low-order multi-dimensional extension of Stirling’s interpolation formula is used to realize the linearization of nonlinear models. Then the semi-definite programming method is utilized to outer-bound the linearization error, which is incorporated to the process noise and observation noise, to reduce the conservativeness of the estimated boundary. At observation updating stage, each observation noise bounding ellipsoid is replaced by a parallelotope formed by several strips to improve the real-time performance. Then a sub-optimal algorithm is designed based on consecutive intersection of the time-updated ellipsoid by each strip. Furthermore, the computing method for normalized distances from the centre of ellipsoid to each hyperplane is improved to reduce the accumulative error, which makes the ellipsoid at each iteration of the current moment participate in the calculation and the optimal value is selected. Simulation results have shown the effectiveness and improved performance of the proposed algorithm. |
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