Research On Attitude Control Of Quadrotor UAV

UAVs have received more and more attention since the beginning of the 21 st century.As a kind of unmanned aerial vehicle with simple structure and vertical take-off and landing,the four-rotor UAV has stimulated people's research enthusiasm and made it every aspect of life will be applied.In this paper,after briefly introducing the research significance of the four-rotor UAV and the research status at home and abroad,the system composition,flight principle,and dynamics modeling of the four-rotor UAV are studied in detail.And designing three kind of PID control,such as cascade PID controller,based on fuzzy rules PID controller and based on the improved BP neural network PID controller,then simulates the three controllers,and each verifies the effectiveness of the attitude angle control.The main research contents and results include the following parts:Firstly,the flight principle of the four-rotor UAV is analyzed in detail.Based on the hovering mode,the dynamics of the UAV is modeled.The LPV criterion is used to linearize the channels of the system.Secondly,the design of the cascade PID controller for the attitude model of the quadrotor UAV is linearized.Combined with the fuzzy rule algorithm in the fuzzy control theory,49 fuzzy rules are established for the PID controller parameter adjustment principle for the control parameters.Micro-adjustment,a PID controller based on fuzzy rules is designed.The attitude angle simulation test and comparison of the two controllers successfully verified the effectiveness of the two controllers for attitude angle control.Thirdly,The traditional BP neural network design model is introduced.The optimization of the learning rate is improved for its inherent deficiencies.The improved BP neural network is combined with the PID controller to design The PID controller based on the improved BP neural network proves that the controller has a faster control effect on the attitude angle control through simulation test.