A tutorial on model predictive control for spacecraft rendezvous

Hartley, Edward N.

doi:10.1109/ecc.2015.7330727

Cited by 34 publications

(19 citation statements)

References 54 publications

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“…Goal of the translational control is to drive the chaser to the docking position, where the target is located, while guaranteeing the satisfaction of the typical position and velocity constraints applied to the proximity maneuver. It is important to precise that the x-y coordinate system of the testbed "coincides" with the x-z orbital plane of (22). In particular, the trajectories should lie in a desired approach cone (see Figure 4), i.e.…”

Section: B Model Of the Planar Experimental Testbedmentioning

confidence: 99%

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An Offline-Sampling SMPC Framework With Application to Autonomous Space Maneuvers

Mammarella

Lorenzen

Capello

et al. 2020

IEEE Trans. Contr. Syst. Technol.

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In this paper, a sampling-based Stochastic Model Predictive Control algorithm is proposed for discrete-time linear systems subject to both parametric uncertainties and additive disturbances. One of the main drivers for the development of the proposed control strategy is the need of reliable and robust guidance and control strategies for automated rendezvous and proximity operations between spacecraft. To this end, the proposed control algorithm is validated on a floating spacecraft experimental testbed, proving that this solution is effectively implementable in real-time. Parametric uncertainties due to the mass variations during operations, linearization errors, and disturbances due to external space environment are simultaneously considered.The approach enables to suitably tighten the constraints to guarantee robust recursive feasibility when bounds on the uncertain variables are provided. Moreover, the offline sampling approach in the control design phase shifts all the intensive computations to the offline phase, thus greatly reducing the online computational cost, which usually constitutes the main limit for the adoption of Stochastic Model Predictive Control schemes, especially for low-cost on-board hardware. Numerical simulations and experiments show that the approach provides probabilistic guarantees on the success of the mission, even in rather uncertain and noise situations, while improving the spacecraft performance in terms of fuel consumption.

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Section: B Model Of the Planar Experimental Testbedmentioning

confidence: 99%

“…Line-Of-Sight constraint defined in terms of infeasible/feasible region considering a minus V-bar approach[22].…”

mentioning

confidence: 99%

An Offline-Sampling SMPC Framework With Application to Autonomous Space Maneuvers

Mammarella

Lorenzen

Capello

et al. 2020

IEEE Trans. Contr. Syst. Technol.

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“…Weiss while optimizing a user defined cost function based on a predictive model for the system dynamics. The ability to explicitly handle multivariable systems, constraints, and performance objectives has rendered MPC very attractive in various fields such as automotive, factory automation, and spacecraft control [3], [4], where it has been proposed for orbital rendezvous [5]- [7], attitude control [8], formation flight [9], and interplanetary transfer [10]. Even though MPC requires higher computational load than conventional closedloop controllers (e.g., PID), linear-quadratic MPC results in quadratic programs that can be solved quickly and efficiently in resource constrained hardware by compact and easyto-verify algorithms, see, e.g., [11] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Opportunities and potential of model predictive control for low-thrust spacecraft station-keeping and momentum-management

Weiss

Cairano

2015

2015 European Control Conference (ECC)

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While electric propulsion generates fuel-efficient thrust for spacecraft control, it can only produce low levels of thrust, necessitating continuous actuation to impart an equivalent impulse to that of chemical thrusters. Thus, many of the standard open-loop propulsion scheduling techniques, developed for impulsive thrust, do not transfer to low-thrust architectures. Continuous actuation, together with tighter anticipated requirements for spacecraft station keeping, e.g., in geostationary Earth orbit (GEO), provides great opportunity for the application of feedback control. We demonstrate that model predictive control (MPC) can provide significant advantages as a control strategy for station keeping of low-thrust spacecraft, provided that its features, such as the capability to enforce output constraints, and the use of a prediction model for the plant and disturbances, are fully exploited. We develop a basic MPC design for station keeping in GEO, and compare its performance with an advanced MPC design that includes output constraints and disturbance prediction. We show that the basic MPC achieves precise regulation, albeit with unsustainable fuel consumption, whereas the advanced MPC satisfies the target mission requirements with fuel consumption in line with that of carefully designed open-loop strategies.

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“…Rendezvous guidance and control under impulsive assumption leads to a venue of works since the beginning of the century (see the review papers [3], [4] control frameworks, Model Predictive Control (MPC) has been the most popular one because it ensures stability while minimizing a flexible objective function (the cost) and satisfying technological constraints (thrusters saturation, safe path constraints, etc.). For instance, different safety requirements have been addressed such as visibility constraints [5], collision or plume avoidance [6], [7], or hovering [8].…”

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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A tutorial on model predictive control for spacecraft rendezvous

Cited by 34 publications

References 54 publications

An Offline-Sampling SMPC Framework With Application to Autonomous Space Maneuvers

An Offline-Sampling SMPC Framework With Application to Autonomous Space Maneuvers

Opportunities and potential of model predictive control for low-thrust spacecraft station-keeping and momentum-management

Impulsive zone model predictive control for rendezvous hovering phases

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