Distributed Dynamic State Estimation and LQG Control in Resource-Constrained Networks
Distributed Dynamic State Estimation and LQG Control in Resource-Constrained Networks
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DOI：
10.1109/tsipn.2018.2801460
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发表时间：
2018-02
影响因子：
3.2
通讯作者：
Yasin Yılmaz;M. N. Kurt;Xiaodong Wang
中科院分区：
文献类型：
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作者：
Yasin Yılmaz;M. N. Kurt;Xiaodong Wang
分析了资源受限网络系统的离散分布式动态状态估计和线性二次型高斯(LQG)控制问题。按照整体的方法，我们为问题中涉及的信号处理、通信和控制任务提供了完整的系统设计，并对它们的性能进行了评估。在存在一个控制器节点和多个传感器节点的情况下，传感器节点以一种资源高效的方式，使用一种称为水平交叉采样的事件触发采样技术向控制器节点报告它们的信息实体。我们证明了水平交叉采样比传统的时间触发均匀采样的性能提高，以及在将数据传输到控制器之前对数据进行本地处理的优势。特别地，所提出的局部处理和跨水平采样的分散格式确保了误差有界的最优(集中)估计和控制方案非常接近于最优(集中)估计和控制方案，从而产生了二阶渐近最优性。此外，还考虑了传感器和控制器之间的非理想通信，并针对不同的信道模型提供了最优的调制技术。仿真结果支持了本文的讨论。
In this paper, the discrete-time distributed dynamic state estimation and linear quadratic Gaussian (LQG) control problems are analyzed for resource-constrained networked systems. Following a holistic approach, we provide a complete system design for the signal processing, communication, and control tasks involved in the problems; and evaluate their performance. In the presence of a controller node and a number of sensor nodes, the sensor nodes, in a resource-efficient way, report their information entities to the controller node using an event-triggered sampling technique called level-crossing sampling. We demonstrate the performance gains due to level-crossing sampling over conventional time-triggered uniform sampling, as well as the advantages of processing data locally before transmitting to the controller. In particular, it is shown that the proposed decentralized schemes with local processing and level-crossing sampling ensure a very close approximation, with a bounded error, to the optimum (centralized) estimation and control schemes, and as a result yield order-2 asymptotic optimality. Moreover, nonideal communication between sensors and the controller is considered, and optimal modulation techniques are provided for different channel models. Simulation results are provided to support the presented discussions.