Dissipativity-based distributed fault diagnosis for plantwide chemical processes

Most modern chemical processes consist of a number of process units interconnected with mass and energy flows, often with energy integration and materials recycle loops. As such, faults (process faults, actuator faults, or sensor faults) often propagate to multiple process units (subsystems), causing significant difficulties in fault diagnosis for plantwide systems. In this paper, a general distributed fault diagnosis approach is proposed for plantwide chemical processes, which takes into account the interactions among process units. The distributed fault diagnostic observers are designed to be sensitive to the local faults (local sensitivity) and insensitive to faults in other process units (remote faults insensitivity) and disturbances. The above requirements are formulated as plantwide dissipativity conditions and the gains for the distributed estimators and residual generators are obtained offline by solving a set of linear matrix inequalities. A case study of heat exchanger network is presented to demonstrate the effectiveness of the proposed approach.