Research On Adaptive Trajectory Tracking Control For Fixed-wing UAV

Fixed-wing unmanned aerial vehicles(UAVs)have been widely used in both defense and civilian fields due to their advantages of high flight speed,long endurance,and maneuverability.Therefore,experts and scholars from various countries have conducted a lot of research in the field of fixed-wing UAVs,from the development of manned aircraft to unmanned aircraft.Trajectory tracking control is a popular topic in this area.Trajectory tracking is the basis for fixed-wing UAVs to perform tasks such as patrol and target tracking,so whether the predetermined trajectory can be tracked is crucial to the completion of the task.In addition,fixed-wing UAV systems are underactuated,nonlinear,and strongly coupled among various system states,making it difficult to establish very accurate mathematical models through mechanism.This makes it difficult to design controllers.In addition,fixed-wing UAVs are very susceptible to wind interference during flight.This article focuses on the trajectory tracking control of fixed-wing UAVs and does the following work:(1)Analyzes the flight principles of fixed-wing UAVs and establishes nonlinear dynamic and kinematic models.To facilitate the design of controllers,the balance state of the fixed-wing UAV is set,and the nonlinear model is Taylor-expanded under the balance state,taking only the first term.This results in a linear model of the fixed-wing UAV.Considering the difference between the cruising trajectory and the landing trajectory of the fixed-wing UAV,controllers are designed for different flight phases;(2)Uses internal model control as the landing trajectory controller for fixed-wing UAVs.In order to avoid the influence of system parameter perturbation and model error on the control effect,this paper uses parameter adaptive algorithm to correct the internal model to ensure the accuracy of the model.Since the actual model is not fully reversible,it cannot well suppress the influence of interference and the non-minimum phase of the model.This paper designs an adaptive compensator to compensate the control output by borrowing the idea of the model reference adaptive algorithm.The above two points ensure the stability and anti-interference ability of the system;(3)Uses model predictive control as the cruising trajectory controller for fixed-wing UAVs.First,in order to reduce static error,the state space equation is changed to an incremental form.Secondly,considering that the trajectory changes greatly during the cruising phase,and the timedomain parameters of the model predictive controller are fixed,sometimes good tracking effects cannot be achieved.Therefore,this article designs a parameter matching mechanism,which matches the optimal time-domain parameters according to the current state information of the fixed-wing UAV by judging the size of the error between the current position and the tracking position,so that the controller has a certain adaptability to different expected trajectories;(4)Connects the cone spiral curve and the landing trajectory curve as the expected trajectory for simulation experiments.The simulation results show that the control method proposed in this article can achieve the control goal well.