...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Automatic Control >Kalman Filter for Discrete-Time Stochastic Linear Systems Subject to Intermittent Unknown Inputs
【24h】

Kalman Filter for Discrete-Time Stochastic Linear Systems Subject to Intermittent Unknown Inputs

机译：间歇性未知输入的离散时间随机线性系统的卡尔曼滤波器

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

State estimation of stochastic discrete-time linear systems subject to persistent unknown inputs has been widely studied but only few works have been dedicated to the case where unknown inputs may be simultaneously or sequentially active or inactive. In this technical note, a Kalman filter approach is proposed for state estimation of systems with unknown intermittent inputs. The design is based on the minimisation of the trace of the state estimation error covariance matrix under the constraint that the state estimation error is decoupled from the unknown inputs corrupting the system at the current time. The necessary and sufficient stability conditions are established considering the upper bound of the prediction error covariance matrix.
机译：随机离散离散线性系统受持续未知输入的状态估计已经被广泛研究，但是只有很少的工作致力于未知输入可能同时或顺序激活或不激活的情况。在本技术说明中，提出了一种卡尔曼滤波方法，用于对间歇性输入未知的系统进行状态估计。该设计基于状态估计误差协方差矩阵的迹线最小化，该约束条件是状态估计误差与当前破坏系统的未知输入解耦。考虑预测误差协方差矩阵的上限，建立必要和充分的稳定性条件。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号