![]() Okyere, E., Bousbaine, A., Poyi, G.T., Joseph, A.K., Andrade, J.M.: LQR controller design for quad-rotor helicopters. Rosaldo-Serrano, M.A., Aranda-Bricaire, E.: Trajectory tracking for a commercial quadrotor via time-varying backstepping. Zou, Y., Zhu, B.: Adaptive trajectory tracking controller for quadrotor systems subject to parametric uncertainties. Zhang, Y., Chen, Z., Zhang, X., Sun, Q., Sun, M.: A novel control scheme for quadrotor UAV based upon active disturbance rejection control. Nazaruddin, Y.Y., Andrini, A.D., Anditio, B.: PSO based PID Controller for quadrotor with virtual sensor. In: Chinese Control Conference (CCC), Guangzhou, China, pp. Jing, Q., Chang, Z., Chu, H., Shao, Y., Zhang, X.: Quadrotor attitude control based on fuzzy sliding mode control theory. Lotufo, M.A., Colangelo, L., Perez-Montenegro, C., Canuto, E., Novara, C.: UAV quadrotor attitude control: an ADRC-EMC combined approach. Zhou, J., Cheng, Y., Du, H., Wu, D., Zhu, M., Lin, X.: Active finite-time disturbance rejection control for attitude tracking of quad-rotor under input saturation. 56, 86–101 (2015)Ĭastillo, A., Sanz, R., Garcia, P., Qiu, W., Wang, H., Xu, C.: Disturbance observer-based quadrotor attitude tracking control for aggressive maneuvers. Mokhtari, M.R., Cherki, B.: A new robust control for minirotorcraft unmanned aerial vehicles. Poultney, A., Gong, P., Ashrafiuon, H.: Integral backstepping control for trajectory and yaw motion tracking of quadrotors. Zhao, L., Dai, L., Xia, Y., Li, P.: Attitude control for quadrotors subjected to wind disturbances via active disturbance rejection control and integral sliding mode control. In: IEEE International Conference on Industrial Technology (ICIT), Lyon, France, pp. Yagoub, M.C., Dhillon, B.S.: Feedback linearization approach to fault tolerance for a micro quadrotor. 10(1), 61–70 (2012)ĭong, N., Zhang, W.-Q., Gao, Z.-K.: Research on fuzzy PID shared control method of small brain-controlled uav. 47(3), 171–177 (2019)Įrginer, B., Altuğ, E.: Design and implementation of a hybrid fuzzy logic controller for a quadrotor VTOL vehicle. Zouaoui, S., Mohamed, E., Kouider, B.: Easy tracking of UAV using PID controller. Nascimento, T.P., Saska, M.: Position and attitude control of multi-rotor aerial vehicles: a survey. In: International Conference on Unmanned Aircraft Systems (ICUAS), Atlanta, GA, USA (2013)Ĭastillo, P., Lozano, R., Dzul, A.: Stabilization of a mini rotorcraft with four rotors. Kanistras, K., Martins, G., Rutherford, M.J., Valavanis, K.P.: A survey of unmanned aerial vehicles (UAVs) for traffic monitoring. Pajares, G.: Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs). Senthilnath, J., Dokania, A., Kandukuri, M., Ramesh, K.N., Anand, G., Omkar, S.N.: Detection of tomatoes using spectral-spatial methods in remotely sensed RGB images captured by UAV. We present comparative simulations results in presence of uncertainties where the superiority of the proposed IT2-FCM-based flight control system is shown in comparison with its type-1 fuzzy counterpart. Thus, the proposed IT2-FCM has a qualitative representation as it merges the advantages of IT2 fuzzy logic systems and FCMs. To model the inter-uncertainty of the experts’ opinions, IT2 fuzzy logic systems are utilized as they are powerful tools to model high level of uncertainties. The degree of mutual influences of the concepts is designed with opinions of three experts that take account the dynamics of drone and rules governing proportional integral derivative (PID) controllers. ![]() ![]() The proposed IT2-FCM encompasses all concepts related to drone for a satisfactory path-tracking and stabilizing control performance. In this paper, we propose a novel Interval Type-2 (IT2) Fuzzy Cognitive Map (FCM)-based flight control system to solve the altitude, attitude and position control problems of quadcopters.
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