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CEAS EuroGNC 2026

Recovering Classical Rendezvous Strategies using MPC for Constrained Closed-Loop Guidance
Diogo Silva PhD Candidate, NOVA School of Science and Technology (NOVA-FCT), 2829-516 Caparica, Portugal. Center of Technology and Systems and LASI (UNINOVA-CTS). Doctoral Researcher, Institute for Systems and Robotics (ISR-Lisbon), Instituto Superior Técnico (IST), 1049-001 Lisbon, Portugal.
Pedro Lourenço Section Head Advanced Guidance & Control, GMV Innovating Solutions, Lisbon, Portugal.
Daniel Silvestre Assistant Professor, NOVA School of Science and Technology (NOVA-FCT), Department of Electrical and Computer Engineering, 2829-516 Caparica, Portugal. Researcher, UNINOVA - CTS and LASI, Caparica, Portugal. Researcher, Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa, Lisboa, Portugal.
José F. Briz GNC Engineer, GMV Innovating Solutions, Madrid, Spain.
Abstract:
Future space missions depend on autonomous rendezvous, ranging from human exploration and large-scale in-orbit assembly to debris removal and satellite servicing. Classical strategies such as V- and R-Bar hopping have been extensively used due to their safety guarantees, holding points, and structured phases, yet their implementation has traditionally relied on pre-generated trajectories that are executed in flight. This approach limits adaptability and does not fully exploit modern control techniques, particularly when mission-specific constraints such as Keep Out Zones or spacecraft restrictions must be considered. This work addresses these limitations by proposing a model predictive control formulation for the short-range phase of rendezvous that reconstructs classical V-, R-Bar, and generalized glideslope hopping approaches while recovering them directly in the optimization problem. The proposed framework incorporates additional mission constraints, including Keep Out Zones enforced via Control Barrier Functions, alongside the approaches, ensuring they remain valid under different dynamical models. The results show that the controller is able to autonomously recover the expected classical hopping behaviors, maintain passive abort safety, andsatisfyconstraintsinbothsingle-run and Monte Carlo simulations.
Keywords: Model Predictive Control; Autonomous Rendezvous; Guidance Navigation and Control; Constrained Control
 View PDF CEAS-GNC-2026-048 doi: 10.82124/CEAS-GNC-2026-048


Diogo Silva, Pedro Lourenço, Daniel Silvestre, José F. Briz: Recovering Classical Rendezvous Strategies using MPC for Constrained Closed-Loop Guidance. Proceedings of the 2026 CEAS EuroGNC conference. Madrid, Spain. May 2026. doi: 10.82124/CEAS-GNC-2026-048.
BibTeX entry (UTF-8):

@Incollection{CEAS-GNC-2026-048,
    author = {Silva, Diogo and Lourenço, Pedro and Silvestre, Daniel and Briz, José F.},
    title = {Recovering Classical Rendezvous Strategies using MPC for Constrained Closed-Loop Guidance},
    booktitle = {Proceedings of the 2026 {CEAS EuroGNC} conference},
    address = {Madrid, Spain},
    month = may,
    year = {2026},
    doi = {10.82124/CEAS-GNC-2026-048}
}