A novel design of Unknown Input Observer for fault diagnosis in the Tennessee-Eastman process system to Solve non-minimum phase problem

Abstract

Fault diagnosis has become crucial subject due to the rising demands for reliability on the one side and higher system performance and product quality on the other side. There are various approaches for the goal of fault detection & isolation between which we focus on the unknown input observer since the observer-based schemes have been successfully adopted in a variety of application fields. This paper presents a novel design of Unknown Input Observer (UIO) for actuator fault detection and isolation in Tennessee-Eastman process control system (TE-PCS) to solve non-minimum phase problem. Unlike many previous UIO methods developed in the literature, the proposed scheme can carry out real-time reconstruction of unknown input in the presence of unstable invariant zero (with respect to the relation between the output and the unknown input). We extend the system by augmenting low pass filter in the inputs-outputs path to tackle the non-minimum phase problem and generate robust residuals. Simulation results demonstrate the effectiveness of the proposed design method.