Contents I. Introduction
In The past years, fault detection (FD) and fault-tolerant control (FTC) techniques have been well developed due to the high reliability and safety requirements of industrial processes. Numerous methods have been reported to deal with FD and FTC studies [1]–[4]. Due to the existence of the nonlinearities in real application systems such as circuit systems, mechanical systems, and chemical systems, considerable attention has also been drawn to studying FD and FTC issues for nonlinear systems [5]–[8]. Various types of nonlinear systems with Lipschitz, stochastic, and affine characteristics have been investigated [9]–[11], and many methods such as adaptive method [12], [13] and sliding-mode method [14], [15] have been used for FD and FTC. In [16], a detection scheme of small faults has been presented for discrete-time nonlinear systems with uncertain dynamics using adaptive dynamics learning approach based on radial basis function neural networks. An incipient sensor FD method has been proposed in [17] for nonlinear control systems with observer unmatched uncertainties by employing an interval sliding mode observer. In addition, an adaptive FTC scheme has been proposed in [18] for a class of uncertain nonlinear systems with actuator faults by taking into account the deferred actuator replacement. In [19], an event-triggered robust adaptive sliding mode FTC strategy has been provided for disturbed nonlinear systems to maintain the output tracking performance.
