针对系统模型的不确定性、未知输入扰动和非线性特性,提出一类非线性系统参数估计的故障诊断算法。构造系统故障诊断观测器,采用Lyapunov稳定性定理验证观测器的稳定性,通过Barbalat引理证明满足故障诊断观测器为渐近稳定的表征故障参数的参数估计,并总结了设计算法流程。仿真结果表明,所提出算法具有快速收敛性,对一类非线性系统诊断效果较好。
In the view of the systems model uncertainties, the unknown input disturbances and the non-linear characteristics of the system model, the fault diagnosis algorithm of a class of nonlinear system based on parameter estimation is proposed. A fault diagnosis observer is constructed for the systems considered, and the Lyapunov stability theorem is used to verify that the fault diagnosis observer is steady. The fault diagnosis observer that characters the parameter fault systems converges asymptotically through the Barbalat lemma. Finally, the algorithm procedures are concluded. The simulation results show that the proposed algorithm has the characteristics that it converges quickly, and then has a perfect diagnosis effect on a class of nonlinear systems.