A Real-Time Configuration Approach for an Observer-Based Residual Generator of Fault Detection Systems

Abstract

This paper is concerned with the real-time configuration of fault detection systems by exploiting an gradient optimization scheme. It is known that industrial processes may often encounter some uncertainties or changes of operating points and environment, which would lead to an unsatisfactory fault detection result. To handle this problem, a real-time (or online) configuration strategy is introduced, which plays an important role in ensuring the efficiency of the fault detection method without a high industrial cost. In this paper, a gradient-based iterative optimization scheme is taken into account for the real-time configuration implementation. By utilizing the gradient-based iterative algorithm to minimize the K-gap between the residual generator and the current system, the parameters of the residual generator can be configured from the online input/output data. Based on this, real-time configuration of the residual generator parameters is achieved and, correspondingly, the fault detection performance is guaranteed. Then, a three-tank system, which is relatively common and important in chemical industrial systems, is studied and explored to verify the effectiveness and superiority of the gradient optimization configuration strategy proposed in this work.