Unlike the previous research works analyzing the stability of the T-S （Takagi-Sugeno） fuzzy model, an extension on the stability condition of T-S fuzzy systems with a different strategy is provided. In the strategy ...Unlike the previous research works analyzing the stability of the T-S （Takagi-Sugeno） fuzzy model, an extension on the stability condition of T-S fuzzy systems with a different strategy is provided. In the strategy a new variable, which is relative to the grade of fuzzy membership function, is introduced to the stability analysis and a new stability conclusion is deduced. The definition of stability condition in this paper is different from previous works, though they are similar in form. With the proposed method, the simulation in flight control law shows a better effectiveness.展开更多
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 approa...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.展开更多
基金supported by the Aviation Science Foundation under Grant No.20110776001Zhejiang Provincial Natural Science Foundation under Grants No. Y1100696 and No.R1090052+1 种基金the Fundamental Research Funds for the Central Universities under Grant No.2011QNA4021National Natural Science Foundation of China under Grant No.61070003 and No.61071128
文摘Unlike the previous research works analyzing the stability of the T-S （Takagi-Sugeno） fuzzy model, an extension on the stability condition of T-S fuzzy systems with a different strategy is provided. In the strategy a new variable, which is relative to the grade of fuzzy membership function, is introduced to the stability analysis and a new stability conclusion is deduced. The definition of stability condition in this paper is different from previous works, though they are similar in form. With the proposed method, the simulation in flight control law shows a better effectiveness.
基金supported by the National Natural Science Foundation of China(Nos.61673209,61741313,61304223)the Aeronautical Science Foundation(Nos.2016ZA52009)+1 种基金the Jiangsu Six Peak of Talents Program(No.KTHY-027)the Fundamental Research Funds for the Central Universities(Nos.NJ20160026,NS2017015)
文摘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.
