Abstract | ||
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A trajectory tracking control system for a fixed-wing unmanned aerial vehicle (UAV) is designed in this paper. A nonlinear model with total variables of UAV is introduced, and the corresponding longitudinal linear model and lateral linear model are obtained by using small perturbation method. The trajectory control system is composed of guidance part and attitude control part. The guidance law is to obtain the reference input attitude information, which consists of two information, the one is the desired attitude information obtained from inverse kinematics and dynamics, the other is path tracking error information. Information fusion control (IFC) method, derived by the fusion estimation theory in multi-sensor data fusion domain, is applied to the attitude control loop, by utilizing two linear models. The simulation results of a nonlinear model described UAV show that it satisfies necessary requirements for achieving good performance in trajectory tracking. |
Year | DOI | Venue |
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2010 | 10.1109/ICNSC.2010.5461505 | ICNSC |
Keywords | Field | DocType |
nonlinear model,lateral linear model,robot dynamics,guidance part,uav flight trajectory control,robot kinematics,unmanned aerial vehicle,attitude control part,inverse kinematics,small perturbation method,inverse dynamics,path tracking error information,mobile robots,longitudinal linear model,aerospace robotics,tracking control system,attitude control,information fusion control method,position control,remotely operated vehicles,fusion estimation theory,sensor fusion,control system,optimal control,satisfiability,control systems,automation,linear model,navigation,estimation theory,trajectory | Optimal control,Inverse kinematics,Linear model,Computer science,Control theory,Attitude control,Sensor fusion,Control engineering,Inverse dynamics,Control system,Trajectory | Conference |
Volume | Issue | ISBN |
null | null | 978-1-4244-6450-0 |
Citations | PageRank | References |
1 | 0.47 | 3 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Ziyang Zhen | 1 | 4 | 2.23 |
Dao Bo Wang | 2 | 21 | 5.92 |
Qi Kang | 3 | 19 | 6.48 |