School of Information Science and Engineering, Shandong Normal University, Jinan, Shandong, 250014, PR China; School of Computing, Engineering and Mathematics, Western Sydney University, Sydney NSW 2751, Australia.
School of Computing, Engineering and Mathematics, Western Sydney University, Sydney NSW 2751, Australia.
ISA Trans. 2019 Dec;95:164-172. doi: 10.1016/j.isatra.2018.11.013. Epub 2018 Dec 7.
This paper considers the estimation problem for periodic systems with unknown measurement input and missing measurements. The missing measurements phenomenon is described by an independent and identically distributed Bernoulli process. The quality of the estimation achieved by an admissible filter is measured by a performance criterion described by the Cesaro limit of the mean square of the deviation between the remote signal and the estimated signal. By employing the minimum variance unbiased estimation technique, the periodic unbiased estimator is obtained, where the estimator gain is designed in terms of the unique periodic solution of a Lyapunov equation together with the periodic stabilizing solution of a Riccati equation. Finally, a numerical example is provided to show the effectiveness of the proposed estimation approach.
本文考虑了具有未知测量输入和缺失测量的周期系统的估计问题。缺失测量现象由独立同分布的伯努利过程描述。可容许滤波器所达到的估计质量由偏差的均方的切萨罗极限来衡量，该偏差是远程信号和估计信号之间的。通过采用最小方差无偏估计技术，得到了周期性无偏估计器，其中估计器增益是根据李雅普诺夫方程的唯一周期解和黎卡提方程的周期稳定解设计的。最后，通过一个数值例子说明了所提出的估计方法的有效性。
