Cooperative distributed model predictive control for embedded systems: Experiments with hovercraft formations
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916654847361024 |
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| author | Stomberg, Gösta Schwan, Roland Grillo, Andrea Jones, Colin N. Faulwasser, Timm |
| author_facet | Stomberg, Gösta Schwan, Roland Grillo, Andrea Jones, Colin N. Faulwasser, Timm |
| contents | This paper presents experiments for embedded cooperative distributed model predictive control applied to a team of hovercraft floating on an air hockey table. The hovercraft collectively solve a centralized optimal control problem in each sampling step via a stabilizing decentralized real-time iteration scheme using the alternating direction method of multipliers. The efficient implementation does not require a central coordinator, executes onboard the hovercraft, and facilitates sampling intervals in the millisecond range. The formation control experiments showcase the flexibility of the approach on scenarios with point-to-point transitions, trajectory tracking, collision avoidance, and moving obstacles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_13334 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Cooperative distributed model predictive control for embedded systems: Experiments with hovercraft formations Stomberg, Gösta Schwan, Roland Grillo, Andrea Jones, Colin N. Faulwasser, Timm Robotics Systems and Control Optimization and Control This paper presents experiments for embedded cooperative distributed model predictive control applied to a team of hovercraft floating on an air hockey table. The hovercraft collectively solve a centralized optimal control problem in each sampling step via a stabilizing decentralized real-time iteration scheme using the alternating direction method of multipliers. The efficient implementation does not require a central coordinator, executes onboard the hovercraft, and facilitates sampling intervals in the millisecond range. The formation control experiments showcase the flexibility of the approach on scenarios with point-to-point transitions, trajectory tracking, collision avoidance, and moving obstacles. |
| title | Cooperative distributed model predictive control for embedded systems: Experiments with hovercraft formations |
| topic | Robotics Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2409.13334 |