Title :
Linear Tracking for a Fixed-Wing UAV Using Nonlinear Model Predictive Control
Author :
Kang, Yeonsik ; Hedrick, J. Karl
Author_Institution :
Dept. of Mech. Eng., Univ. of California, Berkeley, CA, USA
Abstract :
In this paper, a nonlinear model predictive control (NMPC) is used to design a high-level controller for a fixed-wing unmanned aerial vehicle (UAV). Given the kinematic model of the UAV dynamics, which is used as a model of the UAV with low-level autopilot avionics, the control objective of the NMPC is determined to track a desired line. After the error dynamics are derived, the problem of tracking a desired line is transformed into a problem of regulating the error from the desired line. A stability analysis follows to provide the conditions that can assure the closed-loop stability of the designed high-level NMPC. Furthermore, the control objective is extended to track adjoined multiple line segments. The simulation results demonstrate that the UAV controlled by the NMPC converged rapidly with a small overshoot. The performance of the NMPC was also verified through realistic ??hardware in the loop simulation.??
Keywords :
avionics; closed loop systems; control system synthesis; linear systems; nonlinear control systems; optimal control; optimisation; position control; predictive control; remotely operated vehicles; stability; state feedback; NMPC design; adjoined multiple line segment tracking; autopilot avionics; closed-loop stability analysis; fixed-wing UAV dynamics; hardware in-the-loop simulation; kinematic model; linear tracking; nonlinear model predictive control; optimal trajectory; optimization problem; state feedback; unmanned aerial vehicle; Nonlinear model predictive control (NMPC); receding-horizon control; stability; unmanned aerial vehicle (UAV);
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2008.2004878