Two-Stage Observer-Based Fault Detection and Isolation for Re-Entrant Manufacturing Systems

This article investigates the fault detection and isolation (FDI) problem for a class of re-entrant manufacturing systems (RMSs) subject to workstation faults, sensor faults, and measurement disturbances. The system dynamics are first characterized by a hybrid hyperbolic partial differential equation (HHPDE) continuum model. A two-stage observer-based FDI framework is then developed to enable timely and reliable fault diagnosis. In the first stage of this framework, a diagnostic observer equipped with residual evaluation logic is employed, which is capable of detecting the occurrence of faults yet incapable of differentiating between the sensor faults and the workstation faults. Once a fault is detected, the isolation procedure starts as the second stage to distinguish the fault types and localize the fault sources. To be specific, anH-/H∞observer-based isolation scheme is proposed to effectively decouple the sensor faults from the sensor disturbances, by exploiting the dual performance of disturbance attenuation and fault sensitivity; an adaptive observer-based isolation strategy is devised to identify the workstation faults by capturing the associated structural changes in the system dynamics. Finally, the effectiveness and robustness of the proposed methods are validated through comprehensive numerical simulations.