中文摘要：

提出了一种新的基于T—S模糊模型在线辨识的非线性系统的故障诊断与容错控制策略．在闭环控制中，根据在线产生的数据对T—S模糊模型进行辨识，当故障引起系统动态的结构性变化时，在线模糊聚类算法能够辨识出系统的重大改变并产生新的模糊规则描述系统新的动态，同时基于T—S模型的控制律也会做出相应的调整．分析了T—S模糊模型结构和参数调整时闭环系统的稳定性．通过针对倒立摆系统的仿真实验验证了所提方法的有效性．

英文摘要：

A novel fault detection and fault-tolerant control scheme based on online identification of T-S fuzzy model is proposed. In closed-loop control, the T-S fuzzy model is identified through the online generated data of a nonlinear plant. When a fault occurs, the online fuzzy clustering algorithm can detect it by generating new cluster centers, which form new fuzzy rules and change the structure of the control law to accommodate the effect of the fault. Simulation results of an inverted pendulum demonstrate the effectiveness of the proposed fault-tolerant scheme.