Adaptive Trajectories Tracking Control Of UAV Based On Disturbance And Input Saturation Constraint

UAV(unmanned aerial vehicle)is a nonlinear system with under-actuated and strong coupling,which has the advantages of simple structure,low cost and strong maneuverability.UAV is widely used in military,agriculture,detection and other fields,which play a very important role.The control of a quadrotor UAV is a challenge problem.Traditional linear control cannot meet the requirements of high precision of UAV and easily affected by internal and external disturbance.In some cases,UAV also suffers from input saturation limitations.Therefore,nonlinear adaptive controllers are designed to achieve high precision control in the presence of UAV disturbance and input saturation.The specific research work is as follows:(1)The UAV dynamics model is established.Firstly,the basic composition is introduced and the flight principle of the UAV is expounded.The ground coordinate system and the body coordinate system are built and the relationship between the two coordinate systems is determined.Analyzing the disturbance source of UAV.The dynamics model of UAV based on disturbance is deduced according to the rigid body motion theorem.(2)To solve the control problem of UAV under disturbance,an integral backstepping controller is designed.A cascade control scheme is designed to decouple the position loop and attitude loop.Based on the conventional backstepping method,the controller of integral backstepping method is designed with the error integral term.The control parameters of the controller are selected and optimized.The corresponding simulation model is built and the PD,LQR and traditional backstepping controller are designed to carry out comparative experiments.According to the experimental results,it is proved that the integrated backstepping controller has good trajectory tracking ability and anti-interference ability.(3)For the control problem of UAV with both disturbance and input saturation limitation,an adaptive control algorithm based on RBF neural network and antisaturation strategy is designed.Based on the cascade control scheme,the dynamic surface controller is derived and the RBF neural network is introduced to estimate and compensate the disturbance and the anti-saturation strategy is designed to modify the input saturation.Based on the Lyapunov stability theory,the stability of the control scheme was proved by mathematical derivation and the stability interval of the control parameters was given.Furthermore,the simulation model is built.By comparing with PD,LQR and traditional backstepping controller,it is proved that the designed control algorithm has good trajectory tracking ability,anti-interference ability and antisaturation ability.