International audience

The aim of the paper is to propose a navigation strategy applied to a class of rotorcraft having a free rod-suspended load. The presented approach relies on the Linear Kalman Filter to estimate the not only the state vector but also a generalized disturbance term containing parametric, couplings and external uncertainties. A simple hierarchical control is used to drive the motion of the rotorcraft, which is thus updated with the estimation of the disturbance evolving during the a navigation task. Despite the time-scale separation due to the underactuated nature of the flying robot, the estimation approach has shown its effectiveness considering the same sampling time. A detailed simulation model is used to evaluate the performance of the proposal under different disturbed scenarios

International audience

This paper presents a new control method devoted to improve the performances of 2-DOF piezoelectric actuator for precise positioning tasks. The piezoelectric actuator exhibits strong cross-couplings between its two axes and strong hysteresis and creep nonlinearities. These unwanted phenomena undeniably compromised therefore the final precision of the targeted tasks (micromanipulation) and should be conveniently accounted during the controller synthesis. In this paper, we proposed a combination of the discrete linear Kalman filtering with a closed-loop scheme to suppress the effects of the couplings and of the nonlinearities. The suggested method permits to improve the performances of the piezoelectric actuator without specific and detailed characterization and knowledges on the hysteresis and on the creep models. Extensive experiments were carried out with complex desired trajectories and demonstrate the efficiency of the novel approach.

This paper addresses the problem of time optimal path planning for a quadrotor helicopter evolving in a region of known winds. Usually, the flight control of quadrotors subject to wind disturbances challenge seeks to find the optimal control to keep track of a desired trajectory in a windy region. This approach has one major disadvantage: the quadrotor flight control has to compensate for trajectory deviations; therefore, the energy consumption becomes an issue. Most unmanned aerial vehicles (UAV) navigation techniques use waypoints to accomplish their missions. In the framework of a waypoint based navigation, a promising path planning strategy would be a time optimal approach in which the UAV would take advantage of wind to reach its next waypoint; therefore, saving time and energy (under constant forward velocity constraint). A model separation is used to simplify the control of the six-degrees-of-freedom (6DOF) dynamics of the quadrotor. Such approach allows to deal with quadrotor's 3D-motion through two subsystems: dynamic (altitude and MAV-relative forward velocity) and kinematic (nonholonomic navigation) subsystems. In terms of control, a hierarchical control scheme is used to stabilize dynamic and kinematic underactuated subsystems involved in the navigation task. The time optimal path planning is computed using a dynamic optimization method for continuous systems with some state variables specified at an unspecified terminal time. Results have been validated in simulation.