Analysis and Experimentation of Model Predictive Control for Spacecraft Rendezvous and Proximity Operations with Multiple Obstacle Avoidance

Park, Hyeongjun; Zagaris, Costantinos; Virgili-Llop, Josep; Zappulla, Richard; Kolmanovsky, Ilya; Romano, Marcello

doi:10.2514/6.2016-5273

Cited by 26 publications

(29 citation statements)

References 33 publications

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“…Despite this limitation, the results of a similar experimental campaign [10] offer some rough-order-ofmagnitude data for the LQ-MPC approach. In that study, the authors used an LQ-MPC approach to perform docking maneuvers in the presence of two obstacles on the POSEI-DYN test bed.…”

Section: Discussionmentioning

confidence: 99%

“…The fast 5 Hz re-solving rate of IDVD contrasts with the T s = 5 s re-solving period of the LQ-MPC approach. Due to this difference, and given that the LQ-MPC approach is, on average, solved in approximately 0.3 s, with the prediction horizon length set as 20 [10], the computational load of the IDVD approach is significantly larger than the computational load of the LQ-MPC.…”

Section: Discussionmentioning

confidence: 99%

“…The use of MPC has been recently proposed for spacecraft RPO [7] and experimental evaluations using a kinematic test bed have already been conducted [8,9], but to the best knowledge of the authors, this is the first time that the use of MPC is experimentally demonstrated for spacecraft RPO in a dynamically representative test bed. After conducting the experiments presented in this paper, the authors have experimentally demonstrated the use of a nonlinear MPC approach for spacecraft docking maneuvers [10].…”

Section: Introductionmentioning

confidence: 99%

“…In that case, the chaser spacecraft is required to avoid several obstacles before docking with the target. More recently, an LQ-MPC has been compared against a nonlinear MPC for a docking maneuver in the presence of multiple obstacles [10], and a nonlinear MPC approach has been used to experimentally demonstrate docking with a rotating target [20]. Moreover, a near-optimal real-time guidance approach using harmonic potential functions and a modified rapid random tree (RRT) approach has also bee experimentally tested in the POSEIDYN test bed for multiconstrained docking maneuvers [21].…”

Section: Introductionmentioning

confidence: 99%

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Experimental evaluation of model predictive control and inverse dynamics control for spacecraft proximity and docking maneuvers

et al. 2017

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Ground-based experimental evaluations of emerging guidance, navigation, and control (GNC) approaches may be used to raise their technological readiness level and determine their performance and limitations on flight-equivalent hardware (i.e., sensors, actuators, and computational systems) [2].An experimental campaign to evaluate the performance of the model predictive control (MPC) and inverse dynamics in the virtual domain (IDVD) guidance methods has been performed at the Naval Postgraduate School POSEI-DYN 1 air-bearing test bed [4]. The focus of this research is limited in scope to the guidance and control of the simulated spacecraft. The navigation problem is solved by the POSEIDYN test bed motion capture system, which, augmented by onboard sensors, is used to provide accurate navigation data. The test vehicles operating in the POSEI-DYN test bed float on top of a 4-by-4 m granite table and exhibit a drag-free and weightless motion on a plane [4]. These test vehicles are referred to as floating spacecraft simulators, or simply as FSS.A spacecraft docking problem is selected for the experimental evaluation of these two different control approaches. A keep-out zone, an entry cone, and a maximum force constraint are added to the docking scenario to evaluate the constraint handling abilities of the two different controllers. A linear-quadratic MPC (LQ-MPC) algorithm with a quadratic programming (QP) solver and an IDVD algorithm with a nonlinear programming (NLP) solver have been chosen for this comparative study. These two controllers have been implemented and, when executed in real-time on board the FSS, they are successful in 1 POSEIDYN stands for Proximity Operation of Spacecraft: Experimental hardware-In-the-loop DYNamic simulator Abstract An experimental campaign has been conducted to evaluate the performance of two different guidance and control algorithms on a multi-constrained docking maneuver. The evaluated algorithms are model predictive control (MPC) and inverse dynamics in the virtual domain (IDVD). A linear-quadratic approach with a quadratic programming solver is used for the MPC approach. A nonconvex optimization problem results from the IDVD approach, and a nonlinear programming solver is used. The docking scenario is constrained by the presence of a keep-out zone, an entry cone, and by the chaser's maximum actuation level. The performance metrics for the experiments and numerical simulations include the required control effort and time to dock. The experiments have been conducted in a groundbased air-bearing test bed, using spacecraft simulators that float over a granite table.Keywords Rendezvous and proximity operations · Model predictive control · Inverse dynamics · Hardware-in-theloop

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Experimental evaluation of model predictive control and inverse dynamics control for spacecraft proximity and docking maneuvers

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“…For instance, different safety requirements have been addressed such as visibility constraints [5], collision or plume avoidance [6], [7], or hovering [8]. Thanks to MPC properties, stability can be proved even in presence of obstacle avoidance requirements [9]. Robust performances can also be guaranteed using constraint tightening MPC (see [10] and references therein) or tube-based MPC (see [11] and references therein).…”

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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An introductory review of swarm technology for spacecraft on‐orbit servicing

Asri,

Zhu

2024

Int Journal of Mech Sys Dyn

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This review paper presents a comprehensive evaluation and forward‐looking perspective on the underexplored topic of servicing target objects using spacecraft swarms. Such targets can be known or unknown, cooperative or uncooperative, and pose significant challenges in modern space operations due to their inherent complexity and unpredictability. Successfully servicing space objects is vital for active debris removal and broader on‐orbit servicing tasks such as satellite maintenance, repair, refueling, orbital assembly, and construction. Significant effort has been invested in the literature to explore the servicing of targets using a single spacecraft. Given its advantages and benefits, this paper expands the discussion to encompass a swarm approach to the problem. This review covers various single‐spacecraft approaches and presents a critical examination of the existing, although limited, body of work dedicated to servicing orbital objects using multiple spacecraft. The focus is also broadened to include some influential studies concerning the characterization, capture, and manipulation of physical objects by general multiagent systems, a subject with significant parallels to the core interest of this manuscript. Furthermore, this article also delves into the realm of simultaneous localization and mapping, highlighting its application within close‐proximity operations in space, especially when dealing with unknown uncooperative targets. Special attention is paid to the benefits that this field can receive from distributed multiagent architectures. Finally, an exploration of the promising field of swarm robotics is presented, with an emphasis on its potential to revolutionize the servicing of orbital target objects. Concurrently, a survey of general research directly engaging swarms in the orbital context is conducted. This review aims to bridge the knowledge gap and stimulate further research in the underexplored domain of servicing space targets with spacecraft swarms.

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Analysis and Experimentation of Model Predictive Control for Spacecraft Rendezvous and Proximity Operations with Multiple Obstacle Avoidance

Cited by 26 publications

References 33 publications

Experimental evaluation of model predictive control and inverse dynamics control for spacecraft proximity and docking maneuvers

Experimental evaluation of model predictive control and inverse dynamics control for spacecraft proximity and docking maneuvers

Impulsive zone model predictive control for rendezvous hovering phases

An introductory review of swarm technology for spacecraft on‐orbit servicing

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