一类非线性系统故障诊断观测器设计

大多故障诊断算法集中在线性系统方面, 在非线性方面只考虑故障对状态起线性影响的那些系统. 本文根据系统的非线性本质特性, 提出了基于模型的一类非线性系统故障诊断观测器设计方法. 应用系统的(B;K; á)实现精确分解后的系统模型, 对它们的状态故障起非线性的影响. 采用干扰解耦技术,获得的残差对未知扰动有很好的鲁棒性. 在Lyapunov意义下, 验证了算法的稳定性. 仿真验证表明, 所提算法具有快速收敛性, 对一类非线性系统诊断效果较好.

Design of fault diagnosis observer for a class of nonlinear systems

Most of fault diagnosis algorithms deal with linear systems and nonlinear systems with states depending linearly on faults. According to essential properties of a nonlinear system, we propose a fault diagnosis algorithm for a class of nonlinear systems based on parameter estimation. The systems model is decomposed by the (B;K; á) realization into models in which the states are affected nonlinearly by faults. By using the decoupling technology for disturbances, we make the resultant residuals to be completely robust to the unknown input disturbances. Stability of the algorithm is verified by using the Lyapunov function. Simulation results show that the proposed algorithm converges rapidly and provides perfect diagnosis for a class of nonlinear systems.