传感器微小故障诊断及在电机上的应用

为了解决带有未知扰动的微小故障诊断问题,提出一种基于混合未知输入观测器的故障诊断方法。这种观测器不需要已知扰动上界,既可以检测和估计出非线性系统的传感器微小故障,又对未知扰动具有强鲁棒性。首先,通过坐标变换将原系统解耦成两个子系统,其中一个子系统只有传感器微小故障,对其设计观测器进行检测和估计;另一个子系统只有未知扰动,对其设计未知输入观测器消除扰动的影响,且求解未知输入观测器的增益矩阵时减少了约束条件。然后,采用Lyapunov函数证明误差动态方程的稳定性并表示成线性矩阵不等式的形式,有利于观测器增益矩阵的求解。最后,将本文所提方法应用到电机系统中,仿真结果验证了所提方法的有效性。

Diagnosis of Incipient Sensor Faults and Application in Motors

For the purpose of the incipient fault dignosis under disturbances with unknown upper bound, a fault diagnosis method based on the synthetical unknown input observer is put forward, which not only can detect and estimate the incipient sensor fault, but also is robust to disturbances. First, the original system is decoupled into two subsystems by coordinate transformation such that one has only the incipient sensor fault which is detected and estimated by observers and the other has only the disturbance which is eliminated by the unknown input observer, and the constraint conditions of gain matrices are reduced. Then, the stability of the error dynamics is proven by the Lyapunov function and is expressed in the form of linear matrix inequality. Finally, the proposed method is applied to the motor systems and the simulation results show the effectiveness of the proposed method.