Adaptive Threshold Generation for Vehicle Fault Detection Using Switched T–S Interval Observers

Abstract

This paper is concerned with the robust passive fault detection problem for switched continuous-time linear parameter-varying systems with mensurable and unmeasurable scheduling parameters. A switched Takagi–Sugeno (TS) interval observer is designed to estimate the set of admissible state values. Using multiple fuzzy input to state stability-Lyapunov function and average dwell time (ADT) concept, sufficient conditions to guarantee the convergence and the robustness of the proposed observer are obtained. These conditions are formulated as a linear matrix inequality (LMI) problem. In contrast to the existing results based on multiple Lyapunov function and ADT switching, the derived conditions lead to less conservative LMIs characterization. Subsequently, the residual intervals are generated using the designed interval observer and used directly for fault detection (FD) decision making. Finally, the proposed methodology is tested using two examples. First, an academic example is used to illustrate the obtained relaxation. Second, a nonlinear vehicle model corrupted by faults is considered. Longitudinal velocity and cornering stiffness coefficients are treated, respectively, as the measurable and unmeasurable scheduling parameters. Simulation results based on experimental data show the effectiveness of the proposed FD schema.