910 publications from this institution
This article constructs a new fuzzy Lyapunov function (LF) scheme to fault detection (FD) of discrete-time T-S fuzzy models. A fuzzy FD observer is first established to generate residual signals. Then, based on the proposed fuzzy LF, where the membership functions (MFs) of the fuzzy Lyapunov matrix in LF can be used to characterize its forward ones, sufficient conditions in terms of linear matrix inequalities (LMIs) are obtained to guarantee the FD performance of the FD systems. Unlike the existing fuzzy LF methods that depend on the MFs in the T-S models and their forward differences, the Lyapunov inequality in the proposed one can avoid the occurrence of forward differences about the MFs, thus overcoming the shortcomings of the existing results. Finally, two simulation results are shown to verify that the presented technical solution is effective and can achieve better FD results than the existing ones with quadratic LFs.
This article deals with the recursive filtering problem for nonlinear time-varying stochastic systems subject to possible measurement outliers. In order to mitigate the effects from possible abnormal measurements, we construct a filter with a saturation constraint imposed on the innovations where the saturation level is adaptively determined according to the estimation errors. Two performance indices, namely, the finite-horizon H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> specification and the envelope-constraint criterion with a prescribed probability, are put forward to describe the transient characteristics of the filtering error dynamics over a specified time interval. The purpose of the addressed problem is to design a filter capable of guaranteeing both the finite-horizon H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance index and the probability-guaranteed envelope-constraint. Sufficient conditions are derived for the existence of the desired filter via certain convex optimization algorithms. Finally, an illustrative numerical example is proposed to demonstrate the effectiveness of the developed algorithm.
