Chance-constrained Model Predictive Control for Near Rectilinear Halo Orbit spacecraft rendezvous

2025-01-13 · Julio C. Sanchez, Francisco Gavilan, Rafael Vazquez

This work presents a robust Model Predictive Controller (MPC) to solve the problem of spacecraft rendezvous in the context of the restricted three-body problem (R3BP) as will be required to dock with space stations in cislunar space. The employed methodology is both valid for chemical and electric thrusters. By exploiting the state transition matrix and using a chance-constrained approach, the robust MPC assures constraints satisfaction under the presence of disturbances in a probabilistic sense. The perturbations parameters are computed on-line using a disturbance estimator. The robust controller is tested for a rendezvous scenario with a target placed in an Earth-Moon Near-Rectilinear Halo Orbit. Numerical results are shown and discussed.

📄 PDF Abstract BibTeX arXiv:2501.10437

Code (0)

등록된 구현이 없습니다.

Tasks

Model Predictive Controlvalid

Output-Feedback Full-State Targeting Model Predictive Control for Station-Keeping on Near-Rectilinear Halo Orbits

2025-02-07 · Yuri Shimane, Stefano Di Cairano, Koki Ho, Avishai Weiss

We develop a model predictive control (MPC) policy for station-keeping (SK) on a Near-Rectilinear Halo Orbit (NRHO). The proposed policy achieves full-state tracking of a reference NRHO via a two-maneuver control horizon…

Model Predictive Control

Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Control

2026-01-26 · Teruki Kato, Ryotaro Shima, Kenji Kashima arxiv

This paper presents a strictly convex chance-constrained stochastic control framework that accounts for uncertainty in control specifications such as reference trajectories and operational constraints. By jointly optimiz…

Safe Reinforcement Learning with Chance-constrained Model Predictive Control

2021-12-27 · Samuel Pfrommer, Tanmay Gautam, Alec Zhou, Somayeh Sojoudi

Real-world reinforcement learning (RL) problems often demand that agents behave safely by obeying a set of designed constraints. We address the challenge of safe RL by coupling a safety guide based on model predictive co…

Model Predictive Control reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)+1

Recursively Feasible Chance-constrained Model Predictive Control under Gaussian Mixture Model Uncertainty

2024-01-08 · Kai Ren, Colin Chen, Hyeontae Sung, Heejin Ahn 외

We present a chance-constrained model predictive control (MPC) framework under Gaussian mixture model (GMM) uncertainty. Specifically, we consider the uncertainty that arises from predicting future behaviors of moving ob…

Autonomous Driving model Model Predictive Control Trajectory Prediction

A distributionally robust optimization approach to two-sided chance constrained stochastic model predictive control with unknown noise distribution

2022-03-16 · Yuan Tan, Jun Yang, Wen-Hua Chen, Shihua Li

In this work, we propose a distributionally robust stochastic model predictive control (DR-SMPC) algorithm to address the problem of two-sided chance constrained discrete-time linear system corrupted by additive noise. T…