Multi-Instant Gain-Scheduling Fuzzy Observer of Discrete-Time Takagi–Sugeno Systems and Its Application: An Efficient Balanced Matrix Approach
提出一种多时刻增益调度模糊观测器，通过平衡矩阵方法降低状态估计保守性，适用于离散时间Takagi-Sugeno模糊系统的松弛状态估计问题。
The problem of relaxed state estimation of discrete-time Takagi-Sugeno fuzzy systems is studied by constructing a novel multi-instant gain-scheduling fuzzy observer. First, a multi-instant gain-scheduling mechanism with a single adjustable parameter is given for the first time in order to produce more reasonable switch modes over previous results reported in recent literature. Second, for every switch mode, a batch of specified observer gain matrices is determined by developing an efficient balanced matrix approach so that the updated values of adjacent normalized fuzzy weighting functions can be flexibly exploited. Since the implied information of each specific switch mode is capable of being absorbed and utilized more thoroughly by the aid of the refined higher-order balanced matrices, the conservatism can be prominently reduced at the price of consuming extra computational burden within the allowable range. Finally, two benchmark examples are provided to test and verify the progressiveness of our proposed approach.