Controller enhanced fault detection and isolation in a reactor-separator system

Accurate detection and isolation of faults is a critical component of a reliable fault-tolerant control system. It has been demonstrated that using a nonlinear controller to enforce a specific structure in the closed-loop system allows data-based detection and isolation of certain faults that would otherwise not be isolable using data-based techniques without the necessary closed-loop system structure. In this work, we demonstrate through a multi-unit chemical process example how this approach can be applied in a plant- wide setting. Nonlinear, model-based control laws are used to enforce a decoupling structure in the closed-loop system, and data-based statistical process monitoring methods are used for fault detection with isolation of the faults based on the imposed closed-loop system structure.