Development of Small Unmanned Aerial Vehicle and Flight Controller Design

2007 ◽  
Author(s):  
Jin Fujinaga ◽  
Hiroshi Tokutake ◽  
Shigeru Sunada
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Controller Design ◽  
Aerial Vehicle

INTEGRATED PID CONTROLLER DESIGN FOR AN UNMANNED AERIAL VEHICLE WITH STATIC STABILITY

2013 ◽  
Vol 54 (3) ◽  
pp. 200-215 ◽  
Author(s):  
R. LI ◽  
Y. J. SHI ◽  
H. L. XU
Keyword(s):  
Fuzzy Control ◽  
Unmanned Aerial Vehicle ◽  
Pid Controller ◽  
Control Method ◽  
Controller Design ◽  
Design Method ◽  
Design Procedure ◽  
Static Stability ◽  
Aerial Vehicle ◽  
Rolling Mode

AbstractThis paper presents an integrated guidance and control (IGC) design method for an unmanned aerial vehicle with static stability which is described by a nonlinear six-degree-of-freedom (6-DOF) model. The model is linearized by using small disturbance linearization. The dynamic characteristics of pitching mode, rolling mode and Dutch rolling mode are obtained by analysing the linearized model. Furthermore, an IGC design procedure is also proposed in conjunction with a proportional–integral–derivative (PID) control method and fuzzy control method. A PID controller is applied in the control loop of the elevator and aileron, and the attitude angle and attitude angular velocity are used as compensation feedback, giving a simple and low-order control law. A fuzzy control method is applied to perform the cross-coupling control of rolling and yawing. Finally, the 6-DOF simulation shows the effectiveness of the developed method.

Optimal PID controller design with Kalman filter for Qball-X4 quad-rotor unmanned aerial vehicle

2016 ◽  
Vol 39 (12) ◽  
pp. 1785-1797 ◽  
Author(s):  
Feng Pan ◽  
Lu Liu ◽  
Dingyu Xue
Keyword(s):  
Mathematical Model ◽  
Kalman Filter ◽  
Unmanned Aerial Vehicle ◽  
Pid Controller ◽  
Closed Loop ◽  
Controller Design ◽  
Absolute Error ◽  
Pid Controller Design ◽  
Aerial Vehicle ◽  
Set Up

In this paper, we used a Qball-X4 quad-rotor unmanned aerial vehicle (UAV) which was developed by the Quanser Company as the experimental platform. First, a fundamental mathematical model of the Qball-X4 quad-rotor UAV was built and a simulation model was set up based on the proposed mathematical model; then, a double closed-loop optimal proportional–integral–derivative (PID) controller based on integral of time multiplied by absolute error (ITAE) indices was designed according to the model structure. In consideration of the possible system error and data delay, we designed a corresponding Kalman filter, which can estimate the target trajectory and be put before the proposed PID controller to ensure their validity. Finally, simulation results of the system with presented PID controller and Kalman filter were shown to verify their effectiveness.

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