Co-advisor: Isabelle FANTONI
Grant from Mexicain Government
Date PhD finished: November 26th, 2012
Current position: IR at Tell-Environment
This thesis is focused in the design of original and robust control strategies to stabilize
an Unmanned Aerial Vehicle (UAV) in presence of wind disturbances. The proposed
control strategies have been tested in simulations and in real-time experiments
in two different platforms. It introduces the mathematical model of a UAV in presence
of wind. We obtained the dynamical model which takes into account the complementary
forces induced by the wind for a Planar Vertical Take-Off and Landing (PVTOL)
aircraft and for the quadrotor rotorcraft.
On the other hand, three different nonlinear control laws based on the Lyapunov
analysis have been developed to stabilize the UAV in presence of wind. The first approach
uses the Robust Control Lyapunov Functions (RCLFs). Given the complexity
of the problem, we begun with a mini car which moves on its longitudinal axis. This
result has been extended to the case of the PVTOL aircraft and to the quadrotor rotorcraft.
Several simulations have been carried out to validate the proposed algorithms.
To test its viability in a real application, we have realized experiments using a PVTOL
prototype. The simulations and experimental results in real time showed the good
performance of the control law in closed loop.
The second approach is based on the saturation functions. We have proposed a
robust analysis with respect to unknown external disturbances and nonlinear uncertainties
in the model. The proof takes the hypothesis that the wind is bounded. The
algorithms have been tested in a quadrotor prototype and the results showed a good
performance even in presence of wind disturbances.
The last approach considers the intrinsic properties of the quadrotor flying vehicle,
specially the passivity. Thus, a sub-optimal control law has been developed. The
analysis is based on the full energy of the system, the passivity, the Lyapunov theory
and the use of dynamic programming. The simulation results have showed that this
control law can be useful when the flying vehicle has to do more complex maneuvers
Finally, a control scheme using a state observer has been developed. This scheme uses the Extended Kalman Filter (EKF) to estimate the position in the (x,y) plain and the vertical velocity ˙z of a quadrotor rotorcraft. Using the measurements of an inertial measurement unit, an altitude sensor, a vision system and the control inputs the system state is estimated. The vision system is used to compute the translational velocities of the vehicle and it is composed by a camera and an optical flow algorithm. The estimator has been validated by experiments in real time and the results have been very conclusive.