Fault Detection and Isolation Applied to the Supervision of Adaptive Control Systems: A Neural Network Based Scheme

Abstract This paper presents a novel scheme to implement a supervisor for an indirect adaptive control system. The underlying supervisory is performed by using neural networks that heavily borrow from the artificial intelligence culture. Intensive simulations are carried out to emphasize the performance of the proposed supervisor. An experimental study case is examined for demonstrating the applicability of this scheme.