Quadrotor unmanned helicopter is a new popular research platform for unmanned aerial vehicle(UAV),thanks to its simple construction,vertical take-off and landing(VTOL)capability.Here a nonlinear intelligent flight con...Quadrotor unmanned helicopter is a new popular research platform for unmanned aerial vehicle(UAV),thanks to its simple construction,vertical take-off and landing(VTOL)capability.Here a nonlinear intelligent flight control system is developed for quadrotor unmanned helicopter,including trajectory control loop composed of co-controller and state estimator,and attitude control loop composed of brain emotional learning(BEL)intelligent controller.BEL intelligent controller based on mammalian middle brain is characterized as self-learning capability,model-free and robustness.Simulation results of a small quadrotor unmanned helicopter show that the BEL intelligent controller-based flight control system has faster dynamical responses with higher precision than the traditional controller-based system.展开更多
Current applications using single unmanned vehicle have been gradually extended to multiple ones due to their increased efficiency in mission accomplishment, expanded coverage areas and ranges, as well as enhanced sys...Current applications using single unmanned vehicle have been gradually extended to multiple ones due to their increased efficiency in mission accomplishment, expanded coverage areas and ranges, as well as enhanced system reliability. This paper presents a flocking control method with application to a fleet of unmanned quadrotor helicopters （UQHs）. Three critical characteristics of formation keeping, collision avoidance, and velocity matching have been taken into account in the algorithm development to make it capable of accomplishing the desired objectives （like forest/pipeline surveillance） by safely and efficiently operating a group of UQHs. To achieve these, three layered system design philosophy is considered in this study. The first layer is the flocking controller which is designed based on the kinematics of UQH. The modified Cucker and Smale model is used for guaranteeing the convergence of UQHs to flocking, while a repelling force between each two UQHs is also added for ensuring a specified safety distance. The second layer is the motion controller which is devised based on the kinetics of UQH by employing the augmented state-feedback control approach to greatly minimize the steady-state error. The last layer is the UQH system along with its actuators. Two primary contributions have been made in this work： first, different from most of the existing works conducted on agents with double integrator dynamics, a new flocking control algorithm has been designed and implemented on a group of UQHs with nonlinear dynamics. Furthermore, the constraint of fixed neighbouring distance in formation has been relaxed expecting to significantly reduce the complexity caused by the increase of agents number and provide more flexibility to the formation control. Extensive numerical simulations on a group of UQH nonlinear models have been carried out to verify the effectiveness of the proposed method.展开更多
基金supported in part by the National Natural Science Foundation of China(No.61304223)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20123218120015)+1 种基金the Fundamental Research Funds for the Central Universities(No.NZ2015206)the Aeronautical Science Foundation of China(No.2010ZA52002)
文摘Quadrotor unmanned helicopter is a new popular research platform for unmanned aerial vehicle(UAV),thanks to its simple construction,vertical take-off and landing(VTOL)capability.Here a nonlinear intelligent flight control system is developed for quadrotor unmanned helicopter,including trajectory control loop composed of co-controller and state estimator,and attitude control loop composed of brain emotional learning(BEL)intelligent controller.BEL intelligent controller based on mammalian middle brain is characterized as self-learning capability,model-free and robustness.Simulation results of a small quadrotor unmanned helicopter show that the BEL intelligent controller-based flight control system has faster dynamical responses with higher precision than the traditional controller-based system.
文摘Current applications using single unmanned vehicle have been gradually extended to multiple ones due to their increased efficiency in mission accomplishment, expanded coverage areas and ranges, as well as enhanced system reliability. This paper presents a flocking control method with application to a fleet of unmanned quadrotor helicopters （UQHs）. Three critical characteristics of formation keeping, collision avoidance, and velocity matching have been taken into account in the algorithm development to make it capable of accomplishing the desired objectives （like forest/pipeline surveillance） by safely and efficiently operating a group of UQHs. To achieve these, three layered system design philosophy is considered in this study. The first layer is the flocking controller which is designed based on the kinematics of UQH. The modified Cucker and Smale model is used for guaranteeing the convergence of UQHs to flocking, while a repelling force between each two UQHs is also added for ensuring a specified safety distance. The second layer is the motion controller which is devised based on the kinetics of UQH by employing the augmented state-feedback control approach to greatly minimize the steady-state error. The last layer is the UQH system along with its actuators. Two primary contributions have been made in this work： first, different from most of the existing works conducted on agents with double integrator dynamics, a new flocking control algorithm has been designed and implemented on a group of UQHs with nonlinear dynamics. Furthermore, the constraint of fixed neighbouring distance in formation has been relaxed expecting to significantly reduce the complexity caused by the increase of agents number and provide more flexibility to the formation control. Extensive numerical simulations on a group of UQH nonlinear models have been carried out to verify the effectiveness of the proposed method.
