Tracking controllers for small UAVs with wind disturbances: Theory and flight results

Jackson, S.; Tisdale, John; Kamgarpour, Maryam; Basso, Brandon; Hedrick, J. Karl

doi:10.1109/cdc.2008.4739415

Cited by 36 publications

(26 citation statements)

References 6 publications

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“…A spatial sliding mode controller is proposed by Jackson et. al [3], in which wind disturbances with known bounds are explicitly considered in their UAV model, and the controller is designed with involvement of wind disturbance. However, the previous mentioned methods suffer from some limitations, mainly concerning distinct aerodynamics between fixed-wing aircrafts and helicopters.…”

Section: Introductionmentioning

confidence: 99%

Design of a gust-attenuation controller for landing operations of Unmanned Autonomous Helicopters

Yang

Pota

Garratt

2009

2009 IEEE International Conference on Control Applications

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This paper presents an innovative and practical approach to controlling heave motion in the presence of acute stochastic atmospheric disturbances during landing operations of an Unmanned Autonomous Helicopter (UAH). A heave motion model of an UAH is constructed for the purpose of capturing dynamic variations of thrust due to horizontal wind gusts. Additionally, through construction of an effective gust estimator, a promising and feasible feedback-feedforward Proportional Differential (PD) controller is developed, based on available measurements from onboard equipment. The controller dynamically and synchronously compensates for aerodynamic variations of heave motion resulting from gust influence, to increase the disturbance-attenuation ability of the UAH in a windy environment. Simulation results justify the reliability and efficiency of the suggested gust estimator when applied to the heave motion model of a small unmanned helicopter, and verify suitability of the recommended control strategy to realistic environmental conditions.

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Section: Introductionmentioning

confidence: 99%

Design of a gust-attenuation controller for landing operations of Unmanned Autonomous Helicopters

Yang

Pota

Garratt

2009

2009 IEEE International Conference on Control Applications

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“…While the single step planning horizon is adequate for the quadrotor platform considered by Hoffmann, longer plans are required for a fixedwing UAV to execute maneuvers such as a 180-degree turn, and to control the non-minimum phase sensor footprint dynamics of a fixed camera [12].…”

Section: Introductionmentioning

confidence: 99%

Particle filter based information-theoretic active sensing

Ryan

Hedrick

2010

Robotics and Autonomous Systems

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“…The path following controller is composed by a spatial sliding mode controller designed to follow a desired aircraft path which places the camera-footprint on the desired locations, and a kinodynamic controller that directly track a camera-footprint path [8]. UAV's yaw-by-rolling and the kinodynamic controller takes this coupling into account to position the sensor footprint on the target at the expense of positioning the UAV off the target.…”

Section: Path Following and Target Recognitionmentioning

confidence: 99%

“…We think of control as a mean to achieve more effective and efficient estimation of features of the world. An example of this reasoning can be found in [8] where a path-following algorithm is designed to enhance image quality by effectively controlling the camera footprint.…”

Section: Introductionmentioning

confidence: 99%

The C3UV testbed for collaborative control and information acquisition using UAVs

Pereira

Hedrick

Sengupta

2013

2013 American Control Conference

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Abstract-In this paper we introduce the Center for Collaborative Control of Unmanned Vehicles (C3UV) testbed for collaborative information acquisition.The C3UV testbed has been used for demonstrating a wide range of information-oriented applications executed by collaborative teams of Unmanned Aerial Vehicles (UAVs).This paper presents the C3UV testbed from an architectural stand-point. The testbed includes a estimation and control architecture and a software architecture. The estimation and control architecture is a set of components that can be composed to perform specific missions. The software architecture supports the execution of estimation and control components and implements the Collaborative Sensing Language -a language for highlevel specification of mission-level controllers for mobile sensor networks with ad-hoc resource pool and dynamic network topology.We show the use of different layers of the architecture using examples from our field experiments and demonstrations. Our heterogeneous teams of UAVs perform several types of missions such as environmental monitoring, pedestrian search and tracking, and river mapping.

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Tracking controllers for small UAVs with wind disturbances: Theory and flight results

Cited by 36 publications

References 6 publications

Design of a gust-attenuation controller for landing operations of Unmanned Autonomous Helicopters

Design of a gust-attenuation controller for landing operations of Unmanned Autonomous Helicopters

Particle filter based information-theoretic active sensing

The C3UV testbed for collaborative control and information acquisition using UAVs

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