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- | Today, the inspection of structures is carried out through visual assessments eected | + | |
- | by qualied inspectors. | + | |
- | dangerous situations. Consequently, | + | |
- | equipped with on-board vision systems is privileged nowadays | + | ====== Laura MUNOZ HERNANDEZ (HDS) ====== |
- | access to unreachable zones. | + | |
- | In this context, | + | \\ |
- | planning, reference trajectories generation and tracking issues | + | \\ |
- | platform. These methods should allow an automation of the | + | |
- | ight in the presence of air | + | **PhD title:** |
- | disturbances and obstacles. Within this framework, we are interested in two kinds of | + | == Stabilisation et commande d’un UAV en présence de rafales de vent == |
- | aerial vehicles | + | |
- | Firstly, | + | |
- | been realized using the second law of newton. | + | \\ |
- | Secondly, | + | |
- | the problem | + | Co-advisor: Isabelle FANTONI \\ |
- | Then, a strategy of trajectory planning based on operational research approaches | + | Grant from __Mexicain Government__ \\ |
- | has been developed. | + | Location: Heudiasyc \\ |
- | Thirdly, the problem | + | Date PhD finished: **November 26th, 2012** \\ |
- | law based on Lyapunov analysis | + | \\ |
- | saturation functions for quad-rotor crafts | + | |
- | All methods | + | Current position: **IR at Tell-Environment ** |
+ | |||
+ | \\ | ||
+ | |||
+ | |||
+ | |||
+ | |||
+ | |||
+ | == Abstract == | ||
+ | |||
+ | This thesis | ||
+ | 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 | ||
+ | of wind. We obtained | ||
+ | forces induced | ||
+ | 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 | ||
+ | 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, | ||
+ | prototype. The simulations and experimental results in real time showed | ||
+ | performance | ||
+ | |||
+ | 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 | ||
+ | specially the passivity. Thus, a sub-optimal control law has been developed. | ||
+ | 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 | ||
+ | than hover. \\ | ||
+ | |||
+ | Finally, a control scheme using a state observer | ||
+ | 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 | ||
+ | conclusive. | ||
+ | |||
+ | \\ | ||
+ | \\ | ||
+ | \\ |