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Quadrotors are one of the Unmanned Aerial Vehicles (UAVs) that have many applications in the aerospace industries which require a high level of accuracy and innovation in control and stability. In this paper, a hybrid control structure is proposed for this system. The sliding mode controller (SMC) is the foundation of this control structure. This controller, despite its high stability capability for nonlinear systems, has two weaknesses: chattering phenomenon and high vulnerability to noise. The proposed solution is to incorporate the SMC and the Fuzzy intelligent controller because of its high flexibility against the changes in the system model conditions. The new Fuzzy-SMC resolves the SMC weaknesses significantly, but it is not optimized due to a lack of access to the system model expert information. In order to optimize the Fuzzy-SMC, it is necessary to have accurate structural information and specification of the system model which are not available for this case. The final proposed solution is to synthesize the Genetic Algorithm (GA) with the Fuzzy-SMC. In GA performance, each Fuzzy rule is regarded as a chromosome and at each stage, the best of chromosomes, containing the fastest responding, are passed on to the next generation as the elite. The rest combine to create the next generation by using combination and mutation methods. Thus, the Fuzzy-SMC operates based on optimized Fuzzy rules. The results of the simulation in MATLAB software clearly show that the state of quadrotor reaches the desired value and location at the appropriate time.

Quadrotor UAV Position and Altitude Tracking Using an Optimized Fuzzy-Sliding Mode Control