Huang Sheng-Juan, Zhang Da-Qing, Guo Liang-Dong, Wu Li-Bing
IEEE Trans Cybern. 2020 May;50(5):2176-2185. doi: 10.1109/TCYB.2018.2884221. Epub 2018 Dec 19.
The convergent estimation for a class of nonlinear Takagi-Sugeno fuzzy systems is concerned, where time-varying process faults and input disturbances are both involved. A convergent estimation mechanism (CEM) based on a set of fuzzy iterative estimation observers is constructed for the nonlinear fuzzy system; meanwhile, the convergence of the mean sequence of estimation errors (for both states and faults) to zero (vector) is proved. However, in the existing literature, the estimation errors can only be proved to be uniformly ultimately bounded when the fault is time varying. In the design procedure, the disturbances on systems in consideration can be isolated effectively in the obtained fuzzy iterative error dynamics through introducing a suitable isolation technique. Numerical examples give the simulation results to show the effectiveness and merits of the proposed CEM.
研究了一类非线性Takagi-Sugeno模糊系统的收敛估计问题，其中同时考虑了时变过程故障和输入干扰。针对该非线性模糊系统，构建了一种基于模糊迭代估计观测器集的收敛估计机制（CEM）；同时，证明了估计误差（状态和故障的估计误差）的均值序列收敛到零（向量）。然而，在现有文献中，当故障为时变时，只能证明估计误差是一致最终有界的。在设计过程中，通过引入合适的隔离技术，可以在得到的模糊迭代误差动态中有效隔离所考虑系统上的干扰。数值例子给出了仿真结果，以表明所提出的CEM的有效性和优点。
