A New Fault Tolerant Nonlinear Model Predictive Controller Incorporating an UKF-Based Centralized Measurement Fusion Scheme

A new Fault Tolerant Controller (FTC) has been presented in this research by integrating a Fault Detection and Diagnosis (FDD) mechanism in a nonlinear model predictive controller framework. The proposed FDD utilizes a Multi-Sensor Data Fusion (MSDF) methodology to enhance its reliability and estimation accuracy. An augmented state-vector model is developed to incorporate the occurred sensor faults and then a UKF algorithm is utilized to estimate the augmented state vector including system states along with the fault terms using a centralized measurement fusion scheme. The designed FDD architecture is then merged with a conventional NMPC to form a Fault-Tolerant Control System (FTCS). A series of sensor fault senarios is conducted on a Continuous Stirred Tank Reactor (CSTR) to comparatively illustrate the superiority of the proposed FTCS in eliminating the miserable impacts of the induced sensor faults against a conventional NMPC.