Neural network and fuzzy logic approach to aircraft reconfigurable control design

Modern aircraft systems require advanced onboard fault detection, isolation and reconfiguration (FDIR) in order to maintain its performance. Current FDIR designs are subject to uncertainty, nonlinearity, and complexity, leading to high false alarm rate and inaccurate feedback control. Recently, the emergence of neural fuzzy technology has generated a great deal of interest in system learning and control. In this paper, we synthesize a FDIR, scheme by combining neural network method with fuzzy logic concept and show the simulation results by using the nonlinear F-16 aircraft model.