“…Other approaches to fractional order fault detection have also been considered and studied, a notable example are the learning based approaches such as neural network Disturbance observers [40], single layer and double layer radial basis function neural networks (RBFNN) [41], and recurrent wavelet fuzzy neural networks (RWFNN) [42]. Other approaches comprise state observers for actuator faults [43] and sensor faults [44,45,46,47], Fractional observers [48], high gain observers [49] and Generalized fractional order observers [50] for robust fault isolation, adaptive non linear observers [51], Non-fragile H ∞ filter for fault detection [52,53], fractional disturbance observers [54].…”