Quadrotor UAV Path Planning And Tracking Control Technology

Due to the light structure,low cost and high flexibility of the quadrotor,it has been applied in the fields of national defense,commerce and agriculture.In order to further promote the application of the quadrotor and make it more reliable to bring convenience to people’s life,there are two key points should be considered including how to design efficient path planning algorithm and improve the accuracy of trajectory tracking.Therefore,from this point of view,this paper focuses on establishing the dynamic model of quadrotor,path planning algorithm based on RRT,disturbance observer compensation based backstepping trajectory tracking control,norm-optimal based iterative learning control.The main contents of this paper are as follows:Firstly,the nonlinear model of quadrotor is established.The airframe coordinate system and the ground coordinate system are established for the quadrotor with cross structure,and the conversion matrix between the two coordinate systems is derived according to the right-hand rule.This paper introduces the airframe structure of quadrotor,and analyzes the airframe motion which is caused by the variation of the rotor speed.Then the force and the torque of quadrotor are analyzed.According to the Newton Euler’s law,the translation and rotation equations of quadrotor are derived,and the nonlinear model is established by combining the component equations of resultant force and resultant torque on three axes of airframe coordinate system.Secondly,in order to make the quadrotor perform tasks more efficiently,a path planning algorithm based on RRT is studied.Firstly,the shortcomings and causes of traditional RRT and RRT~*algorithms are analyzed.Because of the randomness of the sampling steps of these two algorithms,the path will be searched in the invalid space.Therefore,in order to solve this problem,the concept of the Informed RRT~* algorithm is introduced,which reduces the sampling space through the path information of the last iteration.The concept of ellipse sampling in two-dimensional space is given,which makes the whole algorithm find the global optimal path faster.According to the actual flight requirements of quadrotor,the concept is extended to three-dimensional space,and the sampling strategy is designed.Through simulation,the performance of these three algorithms in two-dimensional and three-dimensional space is compared,and the superiority of the Informed RRT~*algorithm is verified.Then,a backstepping trajectory tracking controller based on sliding mode disturbance observer compensation is designed.The nonlinear model of quadrotor is divided into six subsystems including position control loop and attitude control loop.For the problem of quadrotor underdrive,the desired signals of pitch channel and roll channel are calculated.Considering the internal and external disturbance in the actual flight process,a sliding mode disturbance observer is designed to eliminate the disturbance,and its stability is proved.The backstepping controller is designed for each subsystem,and the disturbance observation value is introduced into the control law to compensate the disturbance.The Lyapunov stability theory proves that the designed control law can make the tracking error of the system gradually stable.Aiming at the problem of many parameters and serious coupling in the backstepping controller,PSO algorithm is introduced to optimize the parameters of the backstepping controller.Matlab simulation results show that the disturbance observer,backstepping controller and particle swarm optimization algorithm can effectively improve the tracking performance.Finally,the optimal ILC based on disturbance observer compensation is designed for the discrete system of quadrotor.Aiming at the problem that all the signals collected in the actual flight are discrete signals,the whole system is linearized and discretized successively,and the disturbance that will be suffered in the flight process is also considered,a discrete disturbance observer is designed and its stability is analyzed.By combining the idea of optimal control with iterative learning,the performance index is improved,the whole system is expressed in the form of super vector,the control law is designed,and the tracking error is proved to be asymptotically stable.The good tracking performance and anti-jamming ability of the designed method are verified by simulation.