Fault detection and diagnosis for delay-range-dependent stochastic systems using output PDFs

This paper investigates a new fault detection and diagnosis(FDD) scheme for delay-range-dependent stochastic systems. Compared with classical FDD problem, the measurable information in this paper is supposed to be the output probability density function(PDF), rather than the output itself. By using the square root B-spline approximation technique, the dynamic weight model of the output PDFs is established and the considered problem is converted into a nonlinear FDD problem for stochastic systems with delays. The main objective of this paper is to construct a filter based residual generator such that the fault can be detected and estimated. The FDD criteria is provided on the basis of linear matrix inequalities(LMIs). Besides, to improve the FDD performance, the tuning parameters, slack variables as well as the free-weighting matrices are applied to optimize the FDD criteria. Finally, the simulations are given to demonstrate the effectiveness of the proposed method.