IN recent years,unmanned aerial vehicles(UAVs)have been widely employed in different applications,both military and civilian.Especially,a fast growing civil UAV market is predicted over the next decades.However,most c...IN recent years,unmanned aerial vehicles(UAVs)have been widely employed in different applications,both military and civilian.Especially,a fast growing civil UAV market is predicted over the next decades.However,most currently developed UAVs depend on simple control strategy.They require exact modeling of the UAVs dynamics and are vulnerable to external disturbance.Therefore,there is great展开更多
In this paper, the control problem for a quadrotor helicopter which is subjected to modeling uncertainties and unknown external disturbance is investigated. A new nonlinear robust control strategy is proposed. First, ...In this paper, the control problem for a quadrotor helicopter which is subjected to modeling uncertainties and unknown external disturbance is investigated. A new nonlinear robust control strategy is proposed. First, a nonlinear complementary filter is developed to fuse the raw data from the onboard barometer and the accelerometer to decrease the negative effects from the noise associated with the low-cost onboard sensors Then the adaptive super-twisting methodology is combined with a backstepping method to formulate the nonlinear robust controller for the quadrotor＇s attitude angles and the altitude position. Lyapunov based stability analysis shows that finite time convergence is ensured for the closed-loop operation of the quadrotor＇s roll angle, pitch angle, row angle and the altitude position. Real-time flight experimental results, which are performed on a quadrotor flight testbed, are included to demonstrate the good control performance of the proposed control methodology.展开更多
This paper proposes a new asymptotic attitude tracking controller for an underactuated 3-degree-of-freedom （DOF） laboratory helicopter system by using a nonlinear robust feedback and a neural network （NN） feedforw...This paper proposes a new asymptotic attitude tracking controller for an underactuated 3-degree-of-freedom （DOF） laboratory helicopter system by using a nonlinear robust feedback and a neural network （NN） feedforward term. The nonlinear robust control law is developed through a modified inner-outer loop approach. The application of the NN-based feedforward is to compensate for the system uncertainties. The proposed control design strategy requires very limited knowledge of the system dynamic model, and achieves good robustness with respect to system parametric uncertainties. A Lyapunov-based stability analysis shows that the proposed algorithms can ensure asymptotic tracking of the helicopter＇s elevation and travel motion, while keeping the stability of the closed-loop system. Real-time experiment results demonstrate that the controller has achieved good tracking performance.展开更多
文摘IN recent years,unmanned aerial vehicles(UAVs)have been widely employed in different applications,both military and civilian.Especially,a fast growing civil UAV market is predicted over the next decades.However,most currently developed UAVs depend on simple control strategy.They require exact modeling of the UAVs dynamics and are vulnerable to external disturbance.Therefore,there is great
基金This work was supported by the Key Project of Tianjin Science and Technology Support Program （No. 15ZCZDGX00810）, the Natural Science Foundation of Tianjin （No. 14JCZDJC31900）, and the National Natural Science Foundation of China （Nos. 91748121, 90916004, 60804004）.
文摘In this paper, the control problem for a quadrotor helicopter which is subjected to modeling uncertainties and unknown external disturbance is investigated. A new nonlinear robust control strategy is proposed. First, a nonlinear complementary filter is developed to fuse the raw data from the onboard barometer and the accelerometer to decrease the negative effects from the noise associated with the low-cost onboard sensors Then the adaptive super-twisting methodology is combined with a backstepping method to formulate the nonlinear robust controller for the quadrotor＇s attitude angles and the altitude position. Lyapunov based stability analysis shows that finite time convergence is ensured for the closed-loop operation of the quadrotor＇s roll angle, pitch angle, row angle and the altitude position. Real-time flight experimental results, which are performed on a quadrotor flight testbed, are included to demonstrate the good control performance of the proposed control methodology.
基金supported by the National Natural Science Foundation of China (Nos. 90916004, 60804004)the Program for New Century Excellent Talents in University (No. NCET-09-0590)
文摘This paper proposes a new asymptotic attitude tracking controller for an underactuated 3-degree-of-freedom （DOF） laboratory helicopter system by using a nonlinear robust feedback and a neural network （NN） feedforward term. The nonlinear robust control law is developed through a modified inner-outer loop approach. The application of the NN-based feedforward is to compensate for the system uncertainties. The proposed control design strategy requires very limited knowledge of the system dynamic model, and achieves good robustness with respect to system parametric uncertainties. A Lyapunov-based stability analysis shows that the proposed algorithms can ensure asymptotic tracking of the helicopter＇s elevation and travel motion, while keeping the stability of the closed-loop system. Real-time experiment results demonstrate that the controller has achieved good tracking performance.
