Fault detection and accommodation in dynamic systems using adaptive neuro-fuzzy systems

Fault detection and accommodation plays a very important role in critical applications. A new software redundancy approach based on all adaptive neuro-fuzzy inference system (ANFIS) is introduced. An ANFIS model is used to detect the fault while another model is used to accommodate it. An accurate plant model is assumed with arbitrary additive faults. The two models are trained online using a gradient-based approach. The accommodation mechanism is based on matching the output of the plant with the output of a reference model. Furthermore, the accommodation mechanism does not assume a special type of system or nonlinearity. Simulation studies prove the effectiveness of the new system even when a severe failure occurs. Robustness to noise and inaccuracies in the plant model are also demonstrated