## Abstract
The proposed approach's performance was also tested for several common fault scenarios that may appear during normal PEM system operation. [PERSON] et al. [15] proposed an approach based on a virtual actuator for fault-tolerant control of linear systems subject to time-varying additive actuator faults as well as an external disturbance. The proposed approach assumes that the structure of the nominal controller is known. Even though this approach was used to synthesize a controller for LTI systems, it can easily be modified to accommodate LPV systems. In [16; 17], a H-infinity observer-based approach is designed to estimate states and sensor and/or actuator faults. Based on the synthesized observer, an output feedback fault-tolerant controller is established to guarantee the stability of a satellite attitude system. Recently, a novel observer-based approach for robust stable hybrid fault-tolerant predictive control was proposed by [PERSON] et al. to investigate actuator faults in systems [18]. Recently, the virtual actuator and virtual sensor-based techniques have attracted more attention in dealing with different types of faults for LPV systems. The authors in [19] proposed an LPV virtual sensor design for FTC nonlinear systems, in which the nonlinear system is described as a LPV representation. In this proposed approach, the scheduling parameters for the controller, plant, and reconfiguration blocks are the same. In another approach proposed in [20], the input and the output matrices of the LPV model are set to have dependent parameters while different virtual actuator (VA) and virtual sensor (VS) parameter designs are allowed depending on whether the faults are total or partial. In addition, several practitioners have considered the implementation of a bank of reconfiguration blocks [1] technique in which each fault scenario is considered in the design. The proposed approach, based on predictive control, has shown good performance in handling actuator faults and maintaining robust trajectory tracking. Generally, model predictive control (MPC) is considered to have been one of the most successful advanced control algorithms in many industrial applications over the past few decades [21; 22; 23]. However, the FTC problem has not been fully investigated for model predictive control, and the FTC-MPC topic has recently become attractive to many researchers, with several algorithms being proposed to deal with actuator faults. [PERSON] et al. [24] proposeda model predictive fault-tolerant control (MPFTC) methodology optimized and adjusted by a Genetic algorithm. The proposed methodology was investigated for batch processes under disturbances and partial actuator faults. [PERSON] et al. [25] proposed an actuator fault-tolerance controller based on nonlinear model predictive control systems. In this approach, the viability theory is used to synthesize the controller. [PERSON] et al. [26] proposed a robust constrained model predictive fault-tolerant control methodology for systems subject to uncertainties, unknown disturbances, interval time-varying delays, and partial actuator failures. Similarly, [PERSON] et al. [27] proposed a new methodology for explicit model predictive control of linear discrete-time systems under linear constraints and subject to unknown disturbances, uncertainties, and actuator faults. [PERSON] et al. [28] proposed and presented a state-space model predictive fault-tolerant control methodology for batch processes subject to unknown disturbances and partial actuator faults. It is worth mentioning that most of the proposed approaches based on MPC algorithms for nonlinear discrete-time systems are based on the linearization of systems around operating points, which makes these approaches less accurate compared with nonlinear methodologies. In addition, it can be clearly observed that FTC-based MPC problems have not been fully investigated for LPV discrete-time systems subject to input constraints and sensor/actuator faults.