System Identification of a Quadrotor Micro Air Vehicle

Gremillion, Gregory M.; Humbert, J. Sean

doi:10.2514/6.2010-7644

Cited by 29 publications

(17 citation statements)

References 1 publication

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“…A linearized flight dynamics model was obtained by Gremillion. 12 The kinematics and dynamics are linearized about forward flight with = 1 m/s, and are presented in Appendix A. The full nonlinear kinematic equations are used for simulation.…”

Section: Methodsmentioning

confidence: 99%

Velocity estimation using optic flow and radar

et al. 2011

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This paper presents the development of a static estimator for obtaining state information from optic flow and radar measurements. It is shown that estimates of translational and rotational speed can be extracted using a least squares inversion. The approach is demonstrated in a simulated three dimensional urban environment on an autonomous quadrotor micro-air-vehicle (MAV). The resulting methodology has the advantages of computation speed and simplicity, both of which are imperative for implementation on MAVs due to stringent size, weight, and power requirements.

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Section: Methodsmentioning

confidence: 99%

Velocity estimation using optic flow and radar

et al. 2011

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“…The pole locations for quadrotor vehicle orientation dynamics can be large, on the order of tens of rad/s. 1 If the dynamics of the actuators are on the same order as the vehicle dynamics, performance of the whole closed loop system could be degraded.…”

Section: Electronic Speed Controller (Esc)mentioning

confidence: 99%

Characterization and enhancement of micro brushless DC motor response

Conroy

Kehlenbeck

Humbert

et al. 2014

Micro- And Nanotechnology Sensors, Systems, and Applications VI

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Commercially available speed controllers, motors, and propellers typically comprise the powertrains of many micro aerial robotic systems, such as quadrotor vehicles. As on board state sensing and processing improves, actuation bandwidth is becoming a significant bottleneck that limits the performance of the entire closed loop system. The performance of the commercial products can be greatly enhanced through the implementation of classical control methods directly at the powertrain level. In this paper, reduced order open loop models for three representative commercially available powertrains were estimated and were compared with closed loop equivalents. Further performance improvement is realized by the addition of a static inverse to mitigate the steady state structured uncertainty of the system.

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“…When working with the unique design configuration of a quadrotor the underlying physic can be difficult to abstract and is an uncertain process. It is however of interest to reduce the amount of variables in the modelling situation through effective system identification methods deriving mathematical models from test data (7) . A case to be referred to in terms of modelling parameters of uncertainty is described by A. Raza and S. Etele (8) who developed a UAV test bench for the simulation environment to allow for testing potential techniques under realistic gust conditions.…”

Section: Literature Surveymentioning

confidence: 99%

Design of a quadrotor flight test stand for system identification

2015

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This paper presents the design, development and construction of a flight test stand for a quadrotor UAV. As opposed to alternate forms of UAV, the power plant in the case of the quadrotor serves a dual purpose of control and propulsion. Since control and propulsion are coupled, the power plant (BLDC motor coupled with propeller) was studied in detail using a black box structure. Extractions of motor parameters in previous studies used traditional BLDC motor equations and propeller theory however the accuracy achievable and confidence in the extracted parameters remained questionable. The developed data acquisition process served to satisfy this need by the construction of a test bench that allows for the extraction of the unknown parameters instilling confidence in the modelling process. The established relationships are then used as inputs into a developed six degree of freedom Euler based mathematical model. A mission profile was constructed with distinct phases of which the mathematical model was used to simulate. Each phase in the mission profile excited different modes of the quadrotor dynamics creating an ideal simulation environment in which changes can be implemented and studied.

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System Identification of a Quadrotor Micro Air Vehicle

Cited by 29 publications

References 1 publication

Velocity estimation using optic flow and radar

Velocity estimation using optic flow and radar

Characterization and enhancement of micro brushless DC motor response

Design of a quadrotor flight test stand for system identification

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