Acquatella B., Paul and Kampen, van, Erik-Jan and Chu, Qi Ping (2022) A Sampled-Data Form of Incremental Nonlinear Dynamic Inversion for Spacecraft Attitude Control. In: AIAA SciTech 2022 Forum. AIAA Scitech 2022 Forum, 2022-01-03 - 2022-01-07, San Diego, CA (USA) & Virtual. doi: 10.2514/6.2022-0761. ISBN 978-162410631-6.
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Official URL: https://arc.aiaa.org/doi/abs/10.2514/6.2022-0761
Abstract
This paper presents a sampled–data form of the recently reformulated incremental nonlinear dynamic inversion (INDI) applied for robust spacecraft attitude control. INDI is a combined model– and sensor–based approach mostly applied for attitude control that only requires an accurate control effectiveness model and measurements of the state and some of its derivatives. This results in a reduced dependency on exact knowledge of system dynamics which is known as a major disadvantage of model–based nonlinear dynamic inversion controllers. However, most of the INDI derivations proposed in the literature assume a very high sampling rate of the system and its controller while also not explicitly considering the available sampling time of the digital control computer. Neglecting the sampling time and its effect in the controller derivations can lead to stability and performance issues of the resulting closed–loop nonlinear system. Therefore, our objective is to bridge this gap between continuous–time, highly sampled INDI formulations and their discrete, lowly sampled counterparts in the context of spacecraft attitude control where low sampling rates are common. Our sampled–data reformulation allows explicit consideration of the sampling time via an approximate sampled–data model in normal form widely known in the literature. The resulting sampled–data INDI control is still robust up to a certain sampling time since it remains only sensitive to parametric uncertainties. Simulation experiments for this particular problem demonstrate the bridge considered between INDI formulations which allows for low sampling control rates.
| Item URL in elib: | https://elib.dlr.de/191218/ | ||||||||||||||||
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| Document Type: | Conference or Workshop Item (Speech) | ||||||||||||||||
| Title: | A Sampled-Data Form of Incremental Nonlinear Dynamic Inversion for Spacecraft Attitude Control | ||||||||||||||||
| Authors: |
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| Date: | January 2022 | ||||||||||||||||
| Journal or Publication Title: | AIAA SciTech 2022 Forum | ||||||||||||||||
| Refereed publication: | Yes | ||||||||||||||||
| Open Access: | Yes | ||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||
| In SCOPUS: | Yes | ||||||||||||||||
| In ISI Web of Science: | No | ||||||||||||||||
| DOI: | 10.2514/6.2022-0761 | ||||||||||||||||
| ISBN: | 978-162410631-6 | ||||||||||||||||
| Status: | Published | ||||||||||||||||
| Keywords: | INDI, incremental nonlinear control, attitude control, spacecraft reorientatin, agility, agile maneuvers, slewing, sampled-data control, discrete systems | ||||||||||||||||
| Event Title: | AIAA Scitech 2022 Forum | ||||||||||||||||
| Event Location: | San Diego, CA (USA) & Virtual | ||||||||||||||||
| Event Type: | international Conference | ||||||||||||||||
| Event Start Date: | 3 January 2022 | ||||||||||||||||
| Event End Date: | 7 January 2022 | ||||||||||||||||
| Organizer: | American Institute of Aeronautics and Astronautics Inc. | ||||||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||
| HGF - Program: | Space | ||||||||||||||||
| HGF - Program Themes: | Space System Technology | ||||||||||||||||
| DLR - Research area: | Raumfahrt | ||||||||||||||||
| DLR - Program: | R SY - Space System Technology | ||||||||||||||||
| DLR - Research theme (Project): | R - Systems and Control Innovation Lab [SY], R - Project High-Torque-Wheels | ||||||||||||||||
| Location: | Oberpfaffenhofen | ||||||||||||||||
| Institutes and Institutions: | Institute of System Dynamics and Control > Space System Dynamics | ||||||||||||||||
| Deposited By: | Acquatella B., Paul | ||||||||||||||||
| Deposited On: | 30 Nov 2022 10:52 | ||||||||||||||||
| Last Modified: | 24 Apr 2024 20:52 |
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