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.