线性时变时滞连续-离散描述系统鲁棒故障诊断滤波器设计

Robust fault diagnosis filer design for linear sampled-data descriptor systems with time-varying delay

针对一类线性时变时滞连续-离散描述系统,设计了基于观测器的鲁棒传感器故障诊断滤波器。首先,提出线性时变时滞连续-离散描述系统模型,并将其转化为非奇异离散模型。然后,基于量测残差,设计基于观测器的鲁棒传感器故障诊断滤波器。该滤波器可保证量测残差对于故障及增广扰动具有鲁棒性,即满足鲁棒H_∞性能指标。鉴于滤波器参数矩阵不等式不是标准的线性矩阵不等式,提出锥补线性化算法以解决该问题。引入残差评价函数及阈值以判断故障是否发生。仿真数据表明,设计的故障诊断滤波器能够有效估计出系统的故障。残差对于故障及扰动的鲁棒性能指标均小于给定值1.18,证明了设计的故障诊断滤波器具有较好的鲁棒性,验证了设计方案的有效性。

A robust sensor fault diagnosis filter with non-singular structure is proposed for a class of linear sampled-data descriptor system with state time-varying delay based on an observer. Firstly, a sampled-data descriptor model with time-varying delay is proposed and transformed into a discrete-time non-singular one. Then, a robust sensor fault diagnosis filer with an observer is proposed based on the measurement residual. This filter can guarantee the robustness of the residual against the augmented disturbance and the sensor fault, which means the H_∞ performance index is satisfied. As the matrix inequality of the designed filter parameters does not meet the Linear Matrix Inequality, a cone complementary linearization algorithm is proposed to solve this problem. The residual evaluation function and the threshold are introduced for judging whether the fault occurs or not. Simulation results show that the designed fault diagnosis filter can effectively estimate the fault of the system, and the robust performance indexes of the residual against the fault and the disturbance are all less than the given value of 1.18, which verify the effectiveness of the proposed method.