Micro Aerial Vehicles (MAVs) are limited in their operation outdoors near obstacles by their ability to withstand wind gusts. Currently widespread position control methods such as Proportional Integral Derivative control do not perform well under the influence of gusts. Incremental Nonlinear Dynamic Inversion (INDI) is a sensor-based control technique that can control nonlinear systems subject to disturbances. It was developed for the attitude control of manned aircraft or MAVs. In this paper we generalize this method to the outer loop control of MAVs under severe gust loads. Significant improvements over a traditional Proportional Integral Derivative (PID) controller are demonstrated in an experiment where the quadrotor flies in and out of a windtunnel exhaust at 10 m s. The control method does not rely on frequent position updates, as is demonstrated in an outside experiment using a standard GPS module. Finally, we investigate the effect of using a linearization to calculate thrust vector increments, compared to a nonlinear calculation. The method requires little modeling and is computationally efficient.
@cite_4 developed an altitude controller that utilizes the vertical acceleration measurement. However, they fed the acceleration back, multiplied with a gain, without utilizing the physical relation between thrust and acceleration. In a different paper, they state that their PID position control implementation has little ability to reject disturbances from wind and translational velocity effects @cite_17 . A vertical controller using the INDI principle was developed for a traditional helicopter in simulation by @cite_18 . Only very limited sensor noise was taken into account, which did not require any filtering. Also, in both of these papers, by separating the vertical axis from the lateral axes, coupling can be expected. We show that by inverting the control effectiveness for all axes, accelerations in each of these axes can be controlled.
@cite_18 @cite_4 @cite_17
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This paper presents a novel control algorithm to regulate the aerodynamic thrust produced by fixed-pitch rotors commonly used on small-scale electrically powered multirotor aerial vehicles. The proposed controller significantly improves the disturbance rejection and gust tolerance of rotor thrust control compared to state-of-the-art RPM (revolutions per minute) rotor control schemes. The thrust modeling approach taken is based on a model of aerodynamic power generated by a fixed-pitch rotor and computed in real time on the embedded electronic speed controllers using measurements of electrical power and rotor angular velocity. Static and dynamic flight tests were carried out in downdrafts and updrafts of varying strengths to quantify the resulting improvement in maintaining a desired thrust setpoint. The performance of the proposed approach in flight conditions is demonstrated by a path tracking experiment, where a quadrotor was flown through an artificial wind gust and the trajectory tracking error was measured. The proposed approach for thrust control demonstrably reduced the tracking error compared to classical RPM rotor control. In this paper, we present an onboard monocular vision system for autonomous takeoff, hovering and landing of a Micro Aerial Vehicle (MAV). Since pose information with metric scale is critical for autonomous flight of a MAV, we present a novel solution to six degrees of freedom (DOF) pose estimation. It is based on a single image of a typical landing pad which consists of the letter "H" surrounded by a circle. A vision algorithm for robust and real-time landing pad recognition is implemented. Then the 5 DOF pose is estimated from the elliptic projection of the circle by using projective geometry. The remaining geometric ambiguity is resolved by incorporating the gravity vector estimated by the inertial measurement unit (IMU). The last degree of freedom pose, yaw angle of the MAV, is estimated from the ellipse fitted from the letter "H". The efficiency of the presented vision system is demonstrated comprehensively by comparing it to ground truth data provided by a tracking system and by using its pose estimates as control inputs to autonomous flights of a quadrotor. An original configuration of a small aerial vehicle having eight rotors is presented. Four rotors are devoted to the stabilization of the orientation of the helicopter, and the other four are used to drive the lateral displacements. A precompensation on the roll and pitch angles has been introduced so that the attitude dynamics is practically independent of the translational dynamics. This compensation is directly related to the velocity of the lateral motors. The dynamical model is obtained using the Euler-Lagrange approach. The proposed configuration is particularly useful for image processing since the the camera orientation is held constant. The eight-rotor rotorcraft is simpler to pilot than other rotorcrafts. A control strategy is proposed that uses the optical flow measurements to achieve a hover flight that is robust with respect to perturbations like wind. The new aerial configuration and control strategy have been tested in real-time experiments. This paper proposes the use of a novel control method based on IDA-PBC in order to address the Aerial Physical Interaction (APhI) problem for a quadrotor UAV. The apparent physical properties of the quadrotor are reshaped in order to achieve better APhI performances, while ensuring the stability of the interaction through passivity preservation. The robustness of the IDA-PBC method with respect to sensor noise is also analyzed. The direct measurement of the external wrench-needed to implement the control method-is compared to the use of a nonlinear Lyapunov-based wrench observer and advantages disadvantages of both methods are discussed. The validity and practicability of the proposed APhI method is evaluated through experiments, where for the first time in the literature, a lightweight all-in-one low-cost F T sensor is used onboard of a quadrotor. Two main scenarios are shown: a quadrotor responding external disturbances while hovering (physical human-quadrotor interaction), and the same quadrotor sliding with a rigid tool along an uneven ceiling surface (inspection painting-like task).