论文标题
网络控制系统的MIMO放大和前面的预码
MIMO Amplify-and-Forward Precoding for Networked Control Systems
论文作者
论文摘要
在本文中，我们考虑了MIMO网络控制系统（NCS），其中传感器通过MIMO褪色通道将观察到的MIMO植物状态放大并将观察到的MIMO植物状态转发到遥控器。我们专注于传感器处的MIMO扩增和前向（AF）预编码设计，以最大程度地减少遥控器的加权平均状态估计误差，但受传感器的平均通信功率增益约束。 MIMO AF预编码设计被配制为无限的地平线平均成本马尔可夫决策过程（MDP）。为了处理与MDP相关的维度的诅咒，我们提出了一种新型的连续时间扰动方法，并得出了MDP的渐近最佳闭合形式优先函数。基于此，我们得出了封闭形式的一阶最佳动力学MIMO AF预言解决方案，该解决方案具有事件驱动的控制结构。具体而言，当累积状态估计误差超过动态阈值时，传感器会激活最强的特定型渠道，以将植物状态的动态加权组合传递给控制器。我们进一步建立了确保MIMO NCS稳定性的技术条件，并表明植物状态估计的均方根误差为$ \ MATHCAL {O} \ left（\ frac {1} {\ bar {f}}}} \ right）$，其中$ \ bar {f} $是最大的af af af af af af af af af af af af af af af af af af af af formimo af af formo af af af af af af af fording。
In this paper, we consider a MIMO networked control system (NCS) in which a sensor amplifies and forwards the observed MIMO plant state to a remote controller via a MIMO fading channel. We focus on the MIMO amplify-and-forward (AF) precoding design at the sensor to minimize a weighted average state estimation error at the remote controller subject to an average communication power gain constraint of the sensor. The MIMO AF precoding design is formulated as an infinite horizon average cost Markov decision process (MDP). To deal with the curse of dimensionality associated with the MDP, we propose a novel continuous-time perturbation approach and derive an asymptotically optimal closed-form priority function for the MDP. Based on this, we derive a closed-form first-order optimal dynamic MIMO AF precoding solution, and the solution has an event-driven control structure. Specifically, the sensor activates the strongest eigenchannel to deliver a dynamically weighted combination of the plant states to the controller when the accumulated state estimation error exceeds a dynamic threshold. We further establish technical conditions for ensuring the stability of the MIMO NCS, and show that the mean square error of the plant state estimation is $\mathcal{O}\left(\frac{1}{\bar{F}}\right)$, where $\bar{F}$ is the maximum AF gain of the MIMO AF precoding.
