Robust fault detection and accommodation of the boiler unit using state space neural networks

This paper deals with the application of state space neural network models to fault detection and accommodation of the boiler unit. The work describes two aspects. First one is the fault detection and in this paper to diagnose the fault the three methods are described and compared: simple and adaptive threshold and more robust method which is model error modelling. The second part of the paper describes the approach to fault accommodation based on the so-called instantaneous linearization of the already trained nonlinear state space model of the system. With obtained linear model it is possible to derive a new control law of the boiler unit in order to eliminate the fault effect in the case of faults. All data used in experiments are collected from the simulator of the boiler unit implemented in Matlab/Simulink.