Optimizing the fault diagnosis and fault-tolerant control of selective catalytic reduction hydrothermal aging using the Unscented Kalman Filter observer

The performance of the selective catalytic reduction (SCR) system has been confirmed to be distinctly affected by hydrothermal aging fault. In this paper, an observer based on the Unscented-Kalman-Filter (UKF) algorithm theory is designed to identify the states of hydrothermal aging so that the aging SCR can be more accurately and efficiently diagnosed and fault-tolerant controlled. Furthermore, a model reference adaptive controller (MRAC) based on the theory of Lyapunov is constructed to enhance the fault-tolerant control performance of SCR Simulation, on the basis of the diagnosis information of UKF observer. The simulations and comparisons are performed to verify the performance of aging diagnosis and fault-tolerant control. The corresponding results show that the UKF observer has better estimation accuracy and respond speed for SCR aging, simultaneously, the fault-tolerant control performance of SCR aging is also better.