Wind Speed and Direction Detection by Means of Solid-state Anemometers Embedded on Small Quadcopters

This work describes the application of a compact, MEMS-based, 2D anemometer to the estimation of a quadrotor's airspeed. Correcting for the vehicle's ground speed provided by internal GPS and inertial units allows this low cost, mobile platform to provide local wind speed estimates. A series of initial, bench-top tests were performed to characterize and calibrate the sensor, which is an improved version of a recently proposed and novel device. Additional full-scale wind tunnel experiments were performed with the sensor mounted on a fixed quadrotor to test the effect of the propellers on the sensor's performance. Keywords: wind sensor; quadcopter; MEMS; UA

Wind Speed and Direction Detection by Means of Solid-state Anemometers Embedded on Small Quadcopters

This work describes the application of a compact, MEMS-based, 2D anemometer to the estimation of a quadrotor's airspeed. Correcting for the vehicle's ground speed provided by internal GPS and inertial units allows this low cost, mobile platform to provide local wind speed estimates. A series of initial, bench-top tests were performed to characterize and calibrate the sensor, which is an improved version of a recently proposed and novel device. Additional full-scale wind tunnel experiments were performed with the sensor mounted on a fixed quadrotor to test the effect of the propellers on the sensor's performance

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

This paper describes an algorithm for atmospheric state estimation that is based on a coupling between inertial navigation and flush air data sensing pressure measurements. In this approach, the full navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to directly estimate atmospheric winds and density using a nonlinear weighted least-squares algorithm. The approach uses a high fidelity model of atmosphere stored in table-look-up form, along with simplified models of that are propagated along the trajectory within the algorithm to provide prior estimates and covariances to aid the air data state solution. Thus, the method is essentially a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere and winds are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the discrete-time observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content to the system. The algorithm is then applied to the design of the pressure measurement system for the Mars 2020 mission. The pressure port layout is optimized to maximize the observability of atmospheric states along the trajectory. Linear covariance analysis is performed to assess estimator performance for a given pressure measurement uncertainty. The results indicate that the new tightly-coupled estimator can produce enhanced estimates of atmospheric states when compared with existing algorithms

Design of Flight Control Laws for a Novel Stratospheric Dual-Aircraft Platform

Dual-aircraft platform (DAP) is a novel concept that features two glider-like unmanned aerial systems (UAS) tethered via a thin adjustable cable allowing them to sail back-and-forth, without propulsion, using vertical wind shear. DAP offers the potential of a low-cost atmospheric satellite. This thesis presents the results of an initiative to demonstrate this novel flight concept through modeling, simulation, and flight testing at Embry-Riddle Aeronautical University (ERAU). A realistic simulation environment, described herein, was developed to support the development and testing of flight control systems. This environment includes nonlinear aerodynamic models for the aircraft, a multi-element cable dynamics model, propeller-motor thrust model, control surface actuator models, and permits time-varying wind profiles. This simulator offers both pilot-in-the-loop control and autonomous sailing flight control, and X-Plane interface to provide visualization cues. An intensive flight test program, described herein, was conducted to support the validation of the DAP concept. MAXA Pro 4m gliders were assembled, instrumented, and flight tested in an effort to physically demonstrate the sailing mode of flight. The flight test program described here focuses on the capability to sail with one aircraft (i.e., fly without propulsion) while towing (i.e., pulling) a moving truck as an intermediate step towards the more complex scenario of sailing with two connected aircraft. Two vital elements of the flight software are implemented and analyzed herein. The accuracy of wind estimation techniques is evaluated using flight testing. The robustness of an L1 adaptive controller is evaluated within the flight simulation environment by comparing its performance with a conventional controller

Real-time wind speed estimation and compensation for improved flight

This paper presents the development and experimental validation of a prototype system for online estimation and compensation of wind disturbances onboard small Rotorcraft unmanned aerial systems (RUAS). The proposed approach consists of integrating a small pitot-static system onboard the vehicle and using simple but effective algorithms for estimating the wind speed in real time. The baseline flight controller has been augmented with a feed-forward term to compensate for these wind disturbances, thereby improving the flight performance of small RUAS in windy conditions. The paper also investigates the use of online airspeed measurements in a closed-loop for controlling the RUAS forward motion without the aid of a global positioning system (GPS). The results of more than 80 flights with a RUAS confirm the validity of our approach