Predictive control algorithm for spacecraft rendezvous hovering phases

Gilz, Paulo Ricardo Arantes; Louembet, Christophe

doi:10.1109/ecc.2015.7330847

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…The idea is to provide a validated model predictive control (MPC) algorithm to steer the follower satellite in a fuel-optimal way to the hovering region. The MPC uses a priori knowledge about the dynamics of the relative motion between spacecraft to iteratively compute the control corrections that fulfill fuel-optimality and constraints [7,29].…”

Section: B Model Predictive Control For the Rendezvous Hovering Phasmentioning

confidence: 99%

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Validated Semi-Analytical Transition Matrix for Linearized Relative Spacecraft Dynamics via Chebyshev Polynomials

Gilz

Bréhard

Gazzino

2018

2018 Space Flight Mechanics Meeting

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During guidance and control procedures of orbiting spacecraft, the respect of positioning and space constraints is decisive for successful missions achievement. The development of algorithms capable of fulfilling these constraints is directly related to how precisely the spacecraft trajectories are known. Since accuracy is essential for these procedures, the prevention and estimation of errors arising from approximations and numerical computations become critical. In this context, we consider solving linear ordinary differential equations via rigorous polynomial approximations in Chebyshev series. These are polynomials together with an error bound accounting for both approximation and rounding errors. Our method allows for the computation of validated approximations of the transition matrices describing the evolution of spacecraft trajectories. The proposed approach is employed in the following applications: first, we consider the linearized impulsive rendezvous framework, demonstrating how to use rigorous polynomials approximations to provide a validated propagation of the relative dynamics between spacecraft; this is then exploited for the hovering phases of the spacecraft rendezvous, where we conceive a validated model predictive control based on semi-definite programs. Finally, we propose a semi-analytical transition matrix for a simplified model of geostationary station keeping, linearizing the spacecraft dynamics which take into account the J2 Earth oblateness effect.

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Section: B Model Predictive Control For the Rendezvous Hovering Phasmentioning

confidence: 99%

“…The relative dynamics equations are developed by a new linearization of Equation (28) about the station keeping point (29). Denoting x = x eoe − x sk , the relative state model for the SK problem is computed as follows:…”

Section: B Linearizationmentioning

confidence: 99%

Validated Semi-Analytical Transition Matrix for Linearized Relative Spacecraft Dynamics via Chebyshev Polynomials

Gilz

Bréhard

Gazzino

2018

2018 Space Flight Mechanics Meeting

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“…Nevertheless, with ever advancing computational hardware, and active research into more efficient algorithms, online optimisation has become less of a barrier to application, and there has recently been significant activity in exploiting both the ability to handle constraints and time-varying systems, whilst optimising a given performance metric in the context of spacecraft rendezvous. Examples of how MPC has been employed include: accommodating limited input authority (thrust constraints) [14]- [26]; using non-quadratic cost functions to achieve particular types of behaviour, for example sparse control actions [14], [15], [17], [20], [23], [24], [27]; enforcing line-of-sight constraints [15], [16], [18], [19], [21], [22], [26]; enforcing soft-docking constraints (the approach velocity reduces in line with with distance to the target) [18], [21]; collision avoidance (with the target and obstacles) [14], [16]- [18], [21], [26]; fault-tolerance by constraining open-loop unforced trajectories to achieve passive safety [16], [28]; accommodating time-varying prediction dynamics (such as those describing relative motion in elliptical orbits) [17], [27], [29], [30]; accommodating time-varying objectives and constraints (such as docking with a tumbling or rotating target) [18], [21]; fuel-efficient station or formation keeping [31], [32] and handling interaction between attitude and translation control [17], [22].…”

Section: Introductionmentioning

confidence: 99%

A tutorial on model predictive control for spacecraft rendezvous

Hartley

2015

2015 European Control Conference (ECC)

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This tutorial paper provides a review of recent advances in the field of spacecraft rendezvous using model predictive control (MPC), an advanced optimal control strategy based on on-line constrained optimisation of control inputs based on predictions of future trajectories. Firstly, the rendezvous objectives, and the generic constrained MPC problem formulation are summarised. This is followed by a discussion of how to select the three key ingredients used in an MPC design: the prediction model, the constraints and the cost function. Since MPC implementation relies on finding the solution to constrained optimisation problems in real-time, computational aspects are also briefly examined. The paper concludes with conjecture on ways the use of MPC in this application could be further advanced.

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