Event-Triggered State Estimation: Experimental Performance Assessment and Comparative Study
Event-Triggered State Estimation: Experimental Performance Assessment and Comparative Study
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事件触发状态估计：实验性能评估和比较研究
DOI：
10.1109/tcst.2016.2623776
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发表时间：
2017-09-01
影响因子：
4.8
通讯作者：
Shi, Ling
中科院分区：
文献类型：
--
作者：
Chen, Wentao;Shi, Dawei;Shi, Ling
本文针对一些典型的事件触发条件，对基于事件的状态估计进行了实验和比较研究。在负载磁制动器的永磁直流转矩电机系统上进行了实验。从三个方面进行了比较：1)在不同的传感器-估计器平均通信速率下的性能；2)噪声协方差矩阵估计不准确的影响；3)计算复杂度。对比结果表明，基于创新的调度在估计质量上优于“增量发送”调度，确定性调度在估计性能上优于随机调度。所考虑的估计器对噪声协方差矩阵的估计敏感，并且保持与标准卡尔曼滤波器相似的计算复杂度。
In this brief, an experimental and comparative study of event-based state estimation is performed for some typical event-triggering conditions. The experiments are performed on a magnetic-brake loaded permanent-magnet dc torque motor system. The comparisons are performed from three aspects: 1) performance under different average sensor-to-estimator communication rates; 2) effect of inaccurate estimates of the noise covariance matrices; and 3) computation complexity. The comparative results show that the innovation-based schedules are relatively superior to the “send-on-delta” schedules in terms of estimation quality, and the deterministic schedules have enhanced estimation performance compared with stochastic counterparts. The estimators considered are sensitive to the estimates of the noise covariance matrices, and retain a similar level of computation complexity as that of the standard Kalman filter.