Communication patterning for multi-step TDMA bandwidth allocation using wireless structural control
Communication patterning for multi-step TDMA bandwidth allocation using wireless structural control
复制标题
使用无线结构控制进行多步 TDMA 带宽分配的通信模式
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
R. Andrew Swartz
中科院分区：
文献类型：
--
作者：
Benjamin D. Winter;R. Andrew Swartz
在地震和大风事件期间，结构控制可以提高结构内的居住者舒适度。在传统的结构控制系统中，中央处理器通过传感器阵列的大量布线来获取数据，计算控制力，并命令致动器网络来减少结构中不期望的振动。为了降低与电缆安装相关的成本，多个无线单元可以通过在整个大型无线传感器网络中传送数据来模拟中央计算站来执行相同的计算。在这样的系统中，常见的是单个传感器可能是结构的重要部分的唯一测量源。随着控制网络中传感器数量的增长，在单个控制步骤期间通过固定无线带宽传输所有传感器数据变得越来越困难，需要使用交错数据通信。控制力计算依赖于精确的状态测量或估计。在本文中，提出了一种方法来选择和评估不同的通信组的大小和无线单元的组合，仍然提供准确的状态估计。对于单个无线单元，多个估计器增益被导出并存储在板上，以使用从单元的不同组合接收的交错数据来执行状态估计计算。结果发现，状态估计和控制性能的影响，在每一个时间步长与不同的传感器和传感器组合提供更多的有用信息比其他的网络拓扑结构。传感器布局理论用于形成传感器组，这些传感器组向网络提供一致的高质量输出信息，但仍然利用所有传感器。
Structural control can enhance occupant comfort within structures during earthquakes and high-wind events. In traditional structural control systems, a central processor acquires data through extensive wiring from an array of sensors, calculates control forces, and commands a network of actuators to reduce undesired vibrations in the structure. To reduce costs associated with cable installation, multiple wireless units can perform the same calculations emulating a central computing station by communicating data throughout a large wireless sensor network. In such a system, it is common that a single sensor may be the only measurement source for an important section of a structure. As the number of sensors in a control network grows, it becomes increasingly difficult to transmit all sensor data during a single control step over the fixed wireless bandwidth, necessitating the use of staggered data communication. Control force calculations rely on accurate state measurements or estimates. In this paper, an approach to select and evaluate different communication group sizes and wireless unit combinations that still provide accurate state estimates is presented. With respect to a single wireless unit, multiple estimator gains are derived and stored on-board to perform state-estimation calculations using staggered data received from different combinations of units. It is found that state estimation and control performance are affected by the network topology used at each timestep with different sensors and sensor combinations providing more useful information than others. Sensor placement theory is used to form sensor groups that provide consistently high-quality output information to the network but still utilize all sensors.