| This Paper:Browse 542 Download 37 |
码上扫一扫！ |
| On extended state based Kalman flter for nonlinear time‑varying uncertain systems with measurement bias |
| XiaochengZhang,WenchaoXue,Hai‑TaoFang |
|
|
| (LSC, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China) |
|
| 摘要: |
|
| 关键词: |
| DOI：https://doi.org/10.1007/s11768-021-00034-2 |
|
| 基金项目:This work was partly supported by National Key R&D Program of China (No. 2018YFA0703800), the National Nature Science Foundation of China (Nos. 11931018, 61633003-3) and the Beijing Advanced Innovation Center for Intelligent Robots and Systems (No. 2019IRS09) |
|
| On extended state based Kalman flter for nonlinear time‑varying uncertain systems with measurement bias |
| Xiaocheng Zhang,Wenchao Xue,Hai‑Tao Fang |
| (LSC, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China) |
| Abstract: |
| This paper addresses the state estimation for a class of nonlinear time-varying stochastic systems with both uncertain dynamics and unknown measurement bias. A novel extended state based Kalman flter (ESKF) algorithm is developed to estimate the original state, the uncertain dynamics and the measurement bias. It is shown that the estimation error of the proposed algorithm is bounded in the mean square sense. Also, the estimation of the measurement bias asymptotically converges to its true value, such that the infuence of measurement bias is eliminated. Furthermore, the asymptotic optimality of the estimation result is proved while the uncertain dynamics approaches to a constant vector. Finally, a simulation study for harmonic oscillator system model is provided to illustrate the efectiveness of proposed method. |
| Key words: Extended state observer · Kalman flter · Uncertain dynamics · Measurement bias |
