%0 Journal Article
%T 采用预估L2–L∞滤波器的传感器信号重构<br>Sensor signal reconfiguration using pre-estimated L2–L∞ filter
%A 蔺君
%A 张平
%J 控制理论与应用
%D 2016
%R 10.7641/CTA.2016.50413
%X 对于含有未建模动态的SIMO系统, 本文提出利用预估L2–L∞滤波器实现对故障传感器信号的重构. 通过 建立故障信号与最小相对阶的测量信号间的传递函数阵, 由相对阶最小的测量信号实现对故障传感器信号的预估, 并在此预估信号基础上, 结合L2–L∞滤波器存在条件, 给出预估L2–L∞滤波器设计及其参数求解方法. 通过将预 估L2–L∞滤波器、L2–L∞滤波器及部分状态观测器在飞行器故障传感器信号重构中的对比, 并由蒙特卡洛仿真实 验, 预估L2–L∞滤波器实现的由俯仰角速度对迎角信号的重构精度最高, 且当系统矩阵及控制输入矩阵的未建模 动态在30%及20%内浮动时, 迎角重构误差小于0:1?.<br>For SIMO systems contained unmodeled dynamics, pre-estimated L2–L∞ filter was proposed to to achieve reconfiguration of fault sensor signals. By establishing transfer function matrix of fault sensors’ signals to the measurement with the minimum relative degree, pre-estimated signals of fault sensors were achieved. Combined with the presence of L2–L∞ filter, the design procedure of pre-estimated L2–L∞ filter were given. By contrast with the reconfigurations of aircraft fault sensors’ signals achieving by pre-estimated L2–L∞ filter, L2–L∞ filter and partial state observer and with Monte Carlo simulation tests, the reconfiguration signal, i.e. attack angle reconfigured by pitch angular rate, which achieved by pre- estimated L2–L∞ filter has the highest precision. And the reconfiguration error of attack angle is less than 0.1 degree, while the system and the control input unmodeled dynamics flutter within 30% and 20%.
%K 预估L2–L∞滤波器 信号重构 L2–L∞滤波器 部分状态观测器 解析余度&lt
%K br&gt
%K pre-estimated L2–L∞ filter signal reconfiguration L2–L∞ filter partial state observer analytical redundancy
%U http://jcta.alljournals.ac.cn/cta_cn/ch/reader/view_abstract.aspx?file_no=CCTA150413&flag=1