Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a gro...Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.展开更多
This work studies the trajectory tracking control for unmanned aerial helicopter(UAH)system under both matched disturbance and mismatched ones.Initially,to tackle the strong coupling,an input-output feedback lineariza...This work studies the trajectory tracking control for unmanned aerial helicopter(UAH)system under both matched disturbance and mismatched ones.Initially,to tackle the strong coupling,an input-output feedback linearization method is utilized to simplify the nonlinear UAH system.Secondly,a set of finite-time disturbance observers(FTDOs)are proposed to estimate mismatched disturbances with their successive derivatives,which are utilized to design the feedforward controller via backstepping.Thirdly,as for matched disturbance,by defining the disturbance characterization index(DCI)to determine whether the disturbance is harmful or not for the UAH system,a feedback controller is proposed and a sufficient condition is established to ensure the convergence of the tracking error.Finally,some numerical simulations and comparisons illustrate the validity and advantages of our control scheme.展开更多
文摘Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.
基金This work was supported by National Natural Science Foundations of China(Nos.62073164,61873127,61922042)the Foundation of Equipment Pre-research Project of Key Laboratory(No.61422200306).
文摘This work studies the trajectory tracking control for unmanned aerial helicopter(UAH)system under both matched disturbance and mismatched ones.Initially,to tackle the strong coupling,an input-output feedback linearization method is utilized to simplify the nonlinear UAH system.Secondly,a set of finite-time disturbance observers(FTDOs)are proposed to estimate mismatched disturbances with their successive derivatives,which are utilized to design the feedforward controller via backstepping.Thirdly,as for matched disturbance,by defining the disturbance characterization index(DCI)to determine whether the disturbance is harmful or not for the UAH system,a feedback controller is proposed and a sufficient condition is established to ensure the convergence of the tracking error.Finally,some numerical simulations and comparisons illustrate the validity and advantages of our control scheme.
