Optimal Data Rate for State Estimation of Switched Nonlinear Systems
Optimal Data Rate for State Estimation of Switched Nonlinear Systems
复制标题
切换非线性系统状态估计的最佳数据速率
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
S. Mitra
中科院分区：
文献类型：
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作者：
Hussein Sibai;S. Mitra
状态估计是监测和控制系统的一个基本问题。工程系统通过共享的带宽有限的信道将传感和计算设备互连，因此，估计算法应该努力最佳地使用带宽。提出了切换非线性动力系统状态估计的熵概念，给出了熵的上界，并在切换信号不可观测的情况下给出了状态估计算法。我们的方法依赖于拓扑熵的概念，并使用有限信息下的控制理论的技术。我们表明，所使用的平均比特率是最佳的意义上说，该算法的效率差距是在一个附加常数的差距之间的差距的系统的估计熵和它的已知上限。我们将该算法应用于两个系统模型，并讨论了跟踪模式的数量的性能影响。
State estimation is a fundamental problem for monitoring and controlling systems. Engineering systems interconnect sensing and computing devices over a shared bandwidth-limited channels, and therefore, estimation algorithms should strive to use bandwidth optimally. We present a notion of entropy for state estimation of switched nonlinear dynamical systems, an upper bound for it and a state estimation algorithm for the case when the switching signal is unobservable. Our approach relies on the notion of topological entropy and uses techniques from the theory for control under limited information. We show that the average bit rate used is optimal in the sense that, the efficiency gap of the algorithm is within an additive constant of the gap between estimation entropy of the system and its known upper-bound. We apply the algorithm to two system models and discuss the performance implications of the number of tracked modes.