An Offline-Sampling SMPC Framework with Application to Automated Space Maneuvers
Loading...
Authors
Mammarella, Martina
Lorenzen, Matthias
Capello, Elisa
Park, Hyeongjun
Dabbene, Fabrizio
Guglieri, Giorgio
Romano, Marcello
̈we, Frank Allgo
Subjects
Advisors
Date of Issue
2018-03
Date
Publisher
ArXiv
Language
Abstract
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 dis- turbances due to external space environment are simultaneously considered.distributions. 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.
Type
Preprint
Description
Series/Report No
Department
Mechanical and Aerospace (MAE)
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
14 p.
Citation
Mammarella, Martina, et al. "An offline-sampling SMPC framework with application to automated space maneuvers." arXiv preprint arXiv:1803.01652 (2018)
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.