多输入-多输出网络量化系统的分析与综合研究

Networked systems with quantized information focus on overcoming the capacity constraint of communication channels, which are the recent research hotspot in the control field. Most of existing works concern the single-input and single-output (SISO) systems, because the analytic expression of the H∞ norm of the uncertain multiple-input and multiple-output (MIMO) systems is hard to obtain, which leads to their application is limited. This project will study MIMO networked systems with quantized information from the following four aspects:.Firstly, the problem of the quantized-scheduling feedback control for MIMO systems with one channel constraint is studied by adopting the lifting technique and the robust analysis method. The scheduling strategy and the coarsest quantizer density are obtained. Then, a Markov-based load-varying model of wireless network is established by using the probability statistics method, and the corresponding multi-density quantizer is designed. According to the game theory method, the mixed H2/H∞ quantized control problem is solved for MIMO systems. Furthermore, based on the Chapman-Kolmogorov equation, the state reset sub-optimal filter for MIMO Markov systems over multi-communication channels is designed by utilizing the structure feature of the logarithmic quantizer. Finally, the methods and main results of this project will be verified by numerical simulations and experiments.

网络量化系统集中解决网络传输带宽受限问题，是目前控制领域的研究热点。由于多输入-多输出（MIMO）不确定系统的H∞范数很难解析表达，现有大多数研究只考虑单输入-单输出（SISO）系统，导致其应用范围有限。本项目针对MIMO网络量化系统开展以下四个方面的研究。.首先，利用提升技术和鲁棒控制分析方法，研究单通道传输约束下MIMO系统的量化调度反馈控制问题，给出调度传输策略和最粗糙的量化密度。其次，采用概率统计方法，建立基于Markov链的网络负载时变模型，设计对应的多密度量化器。通过博弈论方法，解决MIMO系统的混合H2/H∞量化控制问题。再次，通过Chapman-Kolmogorov方程，并提取对数量化器的结构特征，设计多通道传输下MIMO Markov系统的状态重置次优滤波器。最后，进行数值仿真和实验验证。

网络量化系统集中解决网络传输带宽受限问题，是目前控制领域的研究热点。由于多输入-多输出（MIMO）不确定系统的H∞范数很难解析表达，现有大多数研究只考虑单输入-单输出（SISO）系统，导致其应用范围有限。.主要研究内容包括：a) 网络量化系统的滤波与控制；b) 网络量化系统的有限域滤波与同步；c) 不可靠网络情况下的滤波与控制；d) 复杂网络状态估计。.在该项目支持下，项目负责人将理论探索与实验研究相结合，展开了深入且具有原创性的研究，形成了信息不完整、通信受限下网络化系统的控制理论体系，并搭建了系统化的实验平台。取得的成果包括：针对通信受限引起的传输通道不可靠问题，设计了随机采样策略和传输调度策略，有效地提高了网络资源的利用率，提出了传输状态依赖的估计器与控制器，成功地提高了远程估计与控制系统的性能；针对非固定耦合结构复杂网络中单个节点无法获取整个网络耦合结构信息的难题，设计了异步与耦合结构局部依赖的状态估计器，极大地降低了复杂网络中的信息孤岛效应对系统性能的影响。