Autonomous Distributed Control Algorithm for Multiple Spacecraft in Close Proximity Operations

McCamish, Shawn B.; Romano, Marcello; Yun, Xiaoping

doi:10.2514/6.2007-6857

Cited by 25 publications

(42 citation statements)

References 10 publications

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“…Fig. 12 is the bird's eye view of the two chasers one target experiment performed using the unmodified LQR/APF of [22]. As foreseen in Section 2.4 the control design drives the chasers in an equilibrium configuration, where thrusting occurs only to oscillate the robots' positions about the respective local minima.…”

Section: Resultsmentioning

confidence: 99%

“…An important improvement made to the software with respect to [22] is the employment of a complete real-time LQR solver.…”

Section: Real-time Lqrmentioning

confidence: 99%

“…The control algorithm combines the efficiency of a linear quadratic regulator (LQR) and robust collision avoidance capability of artificial potential function (APF) control. The algorithm underwent preliminarily on-orbit hardware-in-the-loop testing with MIT's SPHERES, through a single spacecraft experiment [22].…”

Section: Introductionmentioning

confidence: 99%

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Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

2011

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Section: Resultsmentioning

confidence: 99%

“…An important improvement made to the software with respect to [22] is the employment of a complete real-time LQR solver.…”

Section: Real-time Lqrmentioning

confidence: 99%

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Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

2011

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“…The simplicity of the APF-based control algorithms is a good match for spacecraft applications with limited proximity sensors and processing capability. Our research proposed and evaluated a control algorithm that combines the efficiency of a linear quadratic regulator (LQR) with an APF-based collision-avoidance capability [1][2][3][4][5]. The APF-based collision avoidance relies on relative positions and velocities.…”

Section: Overview Of Nps Multiple-spacecraftmentioning

confidence: 99%

“…Naval Postgraduate School (NPS), allows for robust collision avoidance of both moving and stationary obstacles while converging efficiently to a desired position. The promising simulation results led to the integration of the NPS control algorithm [2][3][4][5] into the Synchronized Position Hold Engage and Reorient Experimental Satellites (SPHERES) facility, developed by the Massachusetts Institute of Technology Space Systems Laboratory (MIT SSL) and currently flying onboard the International Space Station (ISS) [6][7][8][9]. First, a three-satellite experiment that requires collision avoidance during a docking maneuver was selected.…”

Section: Nomenclaturementioning

confidence: 99%

Flight Testing of Multiple-Spacecraft Control on SPHERES During Close-Proximity Operations

McCamish¹,

Romano²,

Nolet³

et al. 2009

Journal of Spacecraft and Rockets

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A multiple-spacecraft close-proximity control algorithm was implemented and tested with the Synchronized Position Hold Engage and Reorient Experimental Satellites (SPHERES) facility onboard the International Space Station. During flight testing, a chaser satellite successfully approached a virtual target satellite while avoiding collision with a virtual obstacle satellite. This research contributes to the control of multiple spacecraft for emerging missions, which may require simultaneous gathering, rendezvous, and docking. The unique control algorithm was developed at the U.S. Naval Postgraduate School and integrated onto the Massachusetts Institute of Technology's SPHERES facility. The control algorithm implemented combines the efficiency of the linear quadratic regulator (used for attraction toward goal positions) and the robust collision-avoidance capability of the artificial potential field method (used for repulsion from moving obstacles). The amalgamation of these two control methods into a multiple-spacecraft close-proximity control algorithm yielded promising results, as demonstrated by simulations. Comprehensive simulation evaluation enabled implementation and ground testing of the spacecraft control algorithm on the SPHERES facility. Successful ground testing led to the execution of flight experiments onboard the International Space Station, which demonstrated the proposed algorithm in a microgravity environment. NomenclatureA, B, C = state-space matrices a = acceleration due to linear-quadratic-regulator-and artificial-potential-field-determined control effort a APF = acceleration due to artificial-potential-fielddetermined control effort a LQR = acceleration due to linear-quadratic-regulatordetermined control effort a m = maximum acceleration a obs = acceleration of chaser spacecraft toward an obstacle a x;y;z = acceleration due to the control effort

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Proximity Relative Motion Planning

Lee

Zhu

Ren³

et al. 2014

SpringerBriefs in Optimization

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Autonomous Distributed Control Algorithm for Multiple Spacecraft in Close Proximity Operations

Cited by 25 publications

References 10 publications

Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

Flight Testing of Multiple-Spacecraft Control on SPHERES During Close-Proximity Operations

Proximity Relative Motion Planning

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