Fault Estimation for Fuzzy Delay Systems: A Minimum Norm Least Squares Solution Approach
针对一类具有状态时滞的Takagi-Sugeno模糊系统，提出了一种基于最小范数最小二乘解的故障估计方法，能有效降低状态误差对估计精度的影响，并通过三个例子验证了有效性。
This paper mainly focuses on the problem of fault estimation for a class of Takagi-Sugeno fuzzy systems with state delays. A minimum norm least squares solution (MNLSS) approach is first introduced to establish a fault estimation compensator, which is able to optimize the fault estimator. Compared with most of the existing fault estimation methods, the MNLSS-based fault estimation method can effectively decrease the effect of state errors on the accuracy of fault estimation. Finally, three examples are given to illustrate the effectiveness and merits of the proposed method.