Quadcopter UAV Modeling and Automatic Flight Control Design

The mathematical model of quadcopter-unmanned aerial vehicle(UAV)is derived by using two approaches:One is the Newton-Euler approach which is formulated using classical mechanics;and other is the Euler-Lagrange approach which describes the model in terms of kinetic(translational and rotational)and potential energy.The proposed quadcopter′s non-linear model is incorporated with aero-dynamical forces generated by air resistance,which helps aircraft to exhibits more realistic behavior while hovering.Based on the obtained model,the suitable control strategy is developed,under which two effective flight control systems are developed.Each control system is created by cascading the proportional-derivative(PD)and T-S fuzzy controllers that are equipped with six and twelve feedback signals individually respectively to ensure better tracking,stabilization,and response.Both proposed flight control designs are then implemented with the quadcopter model respectively and multitudinous simulations are conducted using MATLAB/Simulink to analyze the tracking performance of the quadcopter model at various reference inputs and trajectories.

The mathematical model of quadcopter-unmanned aerial vehicle （UAV） is derived by using two approaches： One is the Newton-Euler approach which is formulated using classical meehanics; and other is the Euler-Lagrange approach which describes the model in terms of kinetic （translational and rotational） and potential energy. The proposed quadcopter＇s non-linear model is incorporated with aero-dynamical forces generated by air resistance, which helps aircraft to exhibits more realistic behavior while hovering. Based on the obtained model, the suitable control strategy is developed, under which two effective flight control systems are developed. Each control system is created by cascading the proportional-derivative （PD） and T-S fuzzy controllers that are equipped with six and twelve feedback signals individually respectively to ensure better tracking, stabilization, and response. Both pro- posed flight control designs are then implemented with the quadcopter model respectively and multitudinous simulations are conducted using MATLAB/Simulink to analyze the tracking performance of the quadcopter model at various reference inputs and trajectories.