Research On Trajectory Tracking And Control Of Quadrotor Uav With Suspended Payloads

The modeling and control of quadrotor UAV slung load system has become a research hotspot in recent years.At present,quadrotor UAV is used in many important fields such as rescue and disaster relief,cargo transportation,reconnaissance and monitoring,but carrying slung loads will undoubtedly make the maneuverability and stability of quadrotor UAV deteriorate,and even cause safety problems.Therefore,it is very necessary to make motion planning of slung loads.In order to realize the load trajectory tracking,this thesis carries out mathematical modeling of the quadrotor UAV slung load system,designs the corresponding controller based on the system model,and uses the hybrid optimization function to plan the load trajectory.The main work is as follows:(1)Firstly,the dynamics and kinematics of the quadrotor UAV are modeled.At the same time,the tension and torque models of the quadrotor UAV are presented.On this basis,EulerLagrange method and Newton-Euler method are used to establish the control rigid body model of the quadrotor UAV slung load system,which provides the model basis for the subsequent control system design.(2)In order to control the movement of the slung load,the load position and attitude controller are designed.Considering the saturation problem that may be caused by the load in the process of motion,an Improved and Conditioned Super Twisting Algorithm(ICSTA)with antisaturation characteristics is proposed.Based on this algorithm,the quadrotor attitude loop controller was designed to have a strong resistance to saturation while reducing sliding mode buffeting.The anti-saturation capability and anti-chattering performance of the proposed improved and conditioned super twisting algorithm are verified by simulation.(3)In order to plan the optimal trajectory of the slung load in three-dimensional space,the trajectory planning problem was modeled,and a trajectory planning method of the slung load based on hybrid optimization function was designed.By combining optimization function of Minimum jerk trajectory and Minimum snap trajectory,and introducing error term to construct hybrid optimization function,which made the generated trajectory smooth enough and minimal energy consumption at the same time.Finally,it is verified by simulation experiment.(4)The feasibility of the control system designed in this thesis is verified by experiments.Firstly,the expected trajectory of the load is planned based on the hybrid optimization function,and then multiple load trajectory tracking tests are carried out.The experimental results show that the control system designed in this thesis achieves good control effect,the improved control method reduces the sliding mode chattering,and can achieve good tracking effect under the condition of load mass or rope length change,which proves that the system has strong robustness.In order to further verify the performance of the system,QDrone platform is used to verify the control system designed in this thesis The results show that the maximum tracking error of X axis and Y axis is less than 0.11 m,and the tracking error of Z axis can converge to 0 quickly.