###### Abstract
In another noteworthy work, a new methodology based on decomposing the non-minimum phase aircraft model into a minimum phase part and a non-minimum phase part for output tracking of a vertical take-off and landing (VTOL) aircraft was introduced [29]. Then, an inversion controller was used for the minimum phase part, while an LQR controller for a new simpler non-minimum phase part was applied to accomplish output tracking with stability. Another control approach that appeared in [30] is based on converting the aircraft's longitudinal dynamics from a non-minimum phase to a minimum phase system by redefining the system using acceleration at the instantaneous center-of-rotation (ICR) and then applying the dynamic inversion approach to the converted acceleration dynamics. In the notable works of [31, 32], a different approach to the NMP problem was proposed, which involved designing a feedback control system based on exact and approximate output tracking of aircraft dynamics instead of input-output linearization of the models describing the aircraft dynamics. The LQR controller was also augmented with integrators to obtain zero steady-state error to a particular input [33, 34] and hence converted the regulation problem to the tracking problem. Over the last decade, fractional-order-based control, which consists of non-integer order derivatives and integrals, is one of the research areas that has gained attention due to the continuous demand to obtain precise controllers for plants with complex dynamics [35]. Most of the proposed fractional-based controllers [36] showed better performance than the integer-based controller when applied to the systems represented with fractional-order or non-fractional-order dynamics. On the other hand, some researchers opted for designing robust flight control systems based on the fractional-order approach for classical and optimal controllers, specifically for UAVs. In [37], for example, the actuator fault and external disturbances were successfully compensated online by applying an adaptive and fractional-order sliding mode control (FOSMC) method to a UAV model. In general terms, the fault-tolerant control (FTC) approach is the most important civil aircraft requirement to guarantee an acceptable performance, reliability, and stability when actuator malfunctions occur [38, 39, 40, 41, 42]. One of the two main types of FTC systems is passive FTC (PFTC) [43, 44], which relies on robustness properties of the controller to compensate for some known faults and maintain the stability of the system without fault detection and diagnosis (FDD) and controller reconfiguration (CR) units. The second type, an active fault-tolerant control system (AFTC) studied in [45, 46, 47], requires a fault detection and diagnosis (FDD) unit to provide information about the magnitude and location of the current fault [48]. Then, it reconfigures the controller to maintain the total stability of the system. Some research groups [49, 50], on the other hand, introduced the adaptive-FTC techniques that can accommodate faults without fault detection and isolation (FDI) units. The main contribution of this paper is to develop a new control structure to overcome the performance and robustness limitations of the classical feedback control system when dealing with non-minimum phase dynamics, especially for some fault cases. The focal idea is based on converting non-minimum phase pitch angle dynamics into an approximate minimum phase system. The proposed approach combines the fractional-order integral controller as the feedforward controller to deal with the non-minimum phase nature of aircraft dynamics with the optimal feedback controller to achieve a good closed-loop system performance and stability of the new augmented minimum phase dynamics. The parameters of the proposed controller are calculated by formulating the control problem as a single-objective optimization problem and solving it by a heuristic global optimization technique according to a fitness function.