The Restore-L Servicing Mission

Reed, Benjamin B.

doi:10.2514/6.2016-5478

Cited by 97 publications

(35 citation statements)

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“…In the context of the industrial development of on-orbit services (see [1]), mastering spacecraft rendezvous is a priority and , from the approaching phases to closing maneuvers, the feedback control algorithm is crucial. This work addresses the hovering phase of a rendezvous mission.…”

Section: Introductionmentioning

confidence: 99%

Impulsive zone model predictive control for rendezvous hovering phases

Louembet

González

Gilz

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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In this manuscript, an impulsive zone MPC formulation is proposed to tackle the problem of the spacecraft rendezvous control. The control objective is to maintain the follower spacecraft in a given subspace with respect to a leader vehicle by stabilizing the set of periodic relative orbits included in a given hovering zone. The idea is to incorporate this hovering zone as a target set into the MPC cost function, in order to permit a single MPC formulation and a receding horizon implementation. The control algorithm takes advantages of a relative motion parametrization for which the set of the equilibrium states represent the set of periodic orbits to prove the stability of the hovering zone and to enlarge significantly the domain of attraction. Several simulation results show that, in addition, performances in terms of convergence and fuel consumption are improved in comparison with previous works.

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Section: Introductionmentioning

confidence: 99%

Impulsive zone model predictive control for rendezvous hovering phases

Louembet

González

Gilz

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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“…Accordingly, angles-only navigation represents a clear enabling technology for a variety of advanced multi-satellite mission concepts [1]. These include robust autonomous rendezvous and docking [2,3], improved space situational awareness, advanced distributed aperture science (see, for example, the miniaturized distributed occulter/telescope project in development at Stanford University [4]), and on-orbit servicing of noncooperative spacecraft [5][6][7]. In line with the terminology of the last application, this paper denotes the observing spacecraft as "the servicer" and treats its orbit as the reference about which to describe the relative orbital motion of the target.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Kalman Filtering for Improved Angles-Only Navigation Using Relative Orbital Elements

Sullivan

D’Amico

2017

Journal of Guidance, Control, and Dynamics

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This paper addresses the design and validation of an accurate estimation architecture for autonomous angles-only navigation in orbits of arbitrary eccentricity. The proposed filtering strategy overcomes the major deficiencies of existing approaches in the literature, which mainly focus on applications in near-circular orbits and generally suffer from poor dynamical observability due to linearizing the filter dynamics and measurement models. Consequently, traditional angles-only navigation solutions require conducting known orbital maneuvers to reconcile the ambiguous range. In contrast, the algorithms developed in this work enable accurate maneuver-free reconstruction of the relative orbital motion. This is done through the full exploitation of nonlinearities in the measurement model using the unscented Kalman filter to improve dynamical observability and filter performance. The filter estimates mean relative orbit elements, adopting a state transition matrix subject to secular and long-period J 2 perturbation effects to decouple observable from unobservable parameters. The complete state is then reconciled with the angle measurements in the measurement model through a nonlinear transformation that includes the conversion from mean to osculating orbital elements. The resulting linear dynamics model is supplemented by either first-order Gauss-Markov processes (that is, differential empirical accelerations) or by a covariance-matching approach to online adaptive process noise tuning to increase performance at minimal computational complexity. Finally, the estimation architecture is completed by a novel deterministic algorithm for batch initial relative orbit determination to accurately initialize the sequential filter.

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“…The DARPA initiatives, Phoenix [55] and Robotic Servicing of Geostationary Satellites (RSGS) [21] along with NASA's Restore-L [56] build on the success of Orbital Express [26] to demonstrate servicing capabilities with the Front-End Robotics Enabling Near-Term Demonstration (FREND) robotic arm [57]. The goals of these missions are to demonstrate the servicing of satellites that were not originally built for in-space servicing.…”

Section: B Active Debris Removal and Active On-orbit Servicingmentioning

confidence: 99%