针对以往故障诊断研究中要求故障或故障导数及系统干扰的上界是已知的不足,以及难以同时诊断执行器故障和传感器故障的问题,提出一种自适应未知输入故障诊断观测器,能够同时重构非线性动态系统的执行器故障和传感器故障.首先,利用H_∞性能指标抑制未知输入对故障重构的影响,采用Lyapunov泛函得到观测误差动态系统的稳定性;然后,通过线性矩阵不等式求解观测器增益阵,并实现故障重构;最后,通过直流电机系统的仿真验证了所提出方法的有效性.
For the shortcoming of previous fault diagnosis studies that the upper of faults or faults derivative and disturbance of system should be known, as well as the difficulty to diagnose the actuator faults and sensor faults simultaneously, an adaptive unknown input fault diagnosis observer is proposed, which can reconstruct the actuator faults and sensor faults in nonlinear dynamical system simultaneously. Firstly, an H_∞ performance index is employed to restrain the influence to fault reconstruction caused by the unknown input, and a Lyapunov function is employed to obtain the robust asymptotically stability of the observer error dynamical system. Then, the gain matrices of the observer are solved by using the linear matrix inequality, and fault reconstruction is fulfilled. Finally, results of the simulation on a DC motor system show the effectiveness of the proposed method.