Research On Trajectory Tracking With Guaranteed Robustness And Fast Adaptation For UAVs

The control of trajectory tracking for the unmanned aerial vehicles(UAVs)is an important mode for the autonomous flight control.The algorithms for trajectory tracking are the key to guarantee the UAV tracking the desired trajectory accurately.The algorithms applying in 2D plane have been unable to meet the requirement of the diverse mission and maneuver in complex,dynamic environmens.It is necessary to study more accurate,more fast adaptation and more robust methods for tracking the desired trajectory.The dissertation studies the key technologies about how to improve the accuracy,the speed of adaptation and robustness in the process of trajectory tracking problems: modeling,control and so on.The main work and contributions are summarized as follows:(1)Applying the classical control and adaptive control theory,an improved L1 adaptive control method is proposed to ensure the controlled system to be stabilized and robust in presence of unknow disturbance.In L1 adaptive control architecture,robustness and adaptation are decoupled.The low pass filter introduced in its structure separates the estimation loop from the control loop.This guarantees a fast adaptation and compensation of the unmodeled dynamics while still preserving the stability of the closed-loop system.This dissertation consider the time lag for time varying reference comands.In this paper,we propose a linear or nonlinear proportional,integral and differential augmentation of this controller in order to reduce the observed tracking error,while the transistant performance is also improved compared to the origin method.The improved methods provide highly accurate and robust method for the following study of the trajectory tracking control poblem.(2)The entire solution for trajectory tracking problem is proposed,where the problem is decoupled into inner and outer loop.And the control laws for the outer loop are desined based on the dynamic inverse method,while the controller for the inner loop are designed based on the improved L1 adaptive control method.i)The error dynamic model is derived based on the idear of traking the visual target point on the trajectory,and the general dynamic model of UAV equiped with a typical commercial autopilot is shown.2)The trajectory tracking problem is decoupled into inner and outer loop.And the control laws for the outer loop are desined based on the dynamic inverse method,while the controller for the inner loop are designed based on the improved L1 adaptive control method.The simulation results for the inner controller and the line,spire line,B spline curve tracking show that: the UAV can tracking the desired reference trajectory accurately,and the inner loop controller based on the improved L1 adaptive control method can ensure the UAV to adaptive the disturbance,the effectiveness for the method is verified.(3)The trajectory tracking ptoblem for single UAV is extended to the cooperative trajectory tracking problem of multiple UAVs.The cooperative control problem is described as a classical consensus problem in the field of robots,and the distributed robust coordination law is designed based on proportional and integral method,while the velociy control loop is augmatived by using the improved L1 adaptive control method,thereby,the time and position constraints is guaranteed to achieve consencus.1)the model for cooperative control problem is contructed,the speeds of the vehicles are adjusted based on coordination information exchanged among the vehicles over a supporting communications network to achieve the time and position cooperative of multiple UAVs.2)The distributed robust coordination law is designed based on proportional integral mehod,and in order to avoid the highly oscillatory speed commands in presence of the time-varying network topology,the improved L1 adaptive control method is applied to the speed control loop.Finally,the simulation results show that multiple UAVs achieve the consencus,the effectiveness for the method is verified.(4)Based the autopilot in my laboratory,the trajectory tracking algorithm is realized and verified on the platform.1)the designed inner loop controller and outer loop controller is applying to the autopilot;2)supporting by the X-Plane and SunSnowMultifly,the system which provieds the test platform is contructed.The trajectory tracking algorithm is verified.