Autonomous Localization And Nonlinear Control Of Multi-rotor Unmanned Aerial Vehicle

In recent years,UAV(Unmanned Aerial Vehicle)has been widely used in society because of its small size and good maneuverability.In militarily,UAVs can execute missions such as reconnaissance and attack to enemy targets.For civil use,it is favored by photographers due to the advantage of being able to take pictures at a fixed point.At the same time,it is also gradually being used in fields like agricultural monitoring,pesticide spraying and electric inspection,which could promote society development.Designing a reliable flight algorithm and autonomous positioning and navigation capability is necessary for UAVs to achieve above functions.Therefore,this thesis designs an adaptive robust control algorithm based on immersion-invariance theory and a visual navigation algorithm,which could provide a feasible solution to the problems.A multi-rotor UAV SLAM platform based on Kinect depth camera is designed in this thesis.The visual positioning algorithm and the flight control algorithm are respectively running on different processors to achieve the quick response and reliability of the system.Based on the detecting,matching of feature points and positioning algorithm,the attitude and position information of the UAVs is calculated.Meanwhile,the data collected by the camera are transmitted to the work station to reconstruct environment by 3D point cloud.Experimental results show that the proposed algorithm can be applied to practical application.Secondly,the definition and transformation of the coordinate system for tiltrotor UAV are analyzed.The attitude dynamic model and the altitude dynamic model are derived by the Newton-Euler method,which paves the way for the design of nonlinear control algorithm to achieve high-precision control.Finally,estimating unknown parameter based on immersion and invariance principle compensates for the uncertainties of dynamic model.The disturbance and estimation bias can be rejected by a robust control algorithm based on the integration of the error sign function.Lyapunov analysis shows that the method can guarantee the stability of the system and yield an asymptotic tracking result.Finally,the effectiveness and robustness of the proposed control algorithm is evaluated extensively through experiment results.