Enhancing data‐based fault isolation through nonlinear control

This work focuses on a broad class of nonlinear process systems subject to control actuator faults and disturbances and proposes a method for data‐based fault detection and isolation that explicitly takes into account the design of the feedback control law. This method allows isolating specific faults in the closed‐loop system; fault detection is done using a purely data‐based approach and fault isolation is achieved using the structure of the closed‐loop system as induced by an appropriately designed controller. This is achieved through the design of nonlinear model‐based state‐feedback control laws that decouple the dependency between certain process state variables in the closed‐loop system. In this sense, the proposed approach constitutes a departure from the available data‐based fault detection and isolation techniques which do not take advantage of the design of the feedback control law to enforce a closed‐loop system structure that enhances fault isolation. The theoretical results are demonstrated through simulations of a CSTR and a gas‐phase polyethylene reactor.