Identification-based sensor and actuator fault diagnosis for industrial control systems and its application to HTR-PM

Abstract

This paper studies sensor and actuator fault diagnosis for a class of linear time-invariant (LTI) industrial control systems. Based on the dynamic model obtained using system identification, a method is proposed that can diagnose all sensor and actuator faults in the control system when they do not happen simultaneously. First, a structured residual design method is developed for coupled systems. Then model errors that occur in system identification are considered and the robust isolability is analyzed. Finally, online decision rules are given which are easy to implement. The method does not require fault data and can deal with small faults that cannot be detected by inspecting input–output signals. Verification in the high temperature gas-cooled reactor pebble-bed module (HTR-PM) simulation platform shows good potential of the method for complex industrial control systems.