Sampathirao, Ajay Kumar and Sopasakis, Pantelis and Bemporad, Alberto and Patrinos, Panagiotis GPU-accelerated stochastic predictive control of drinking water networks. Working Paper arXiv (Submitted)
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Official URL: https://arxiv.org/abs/1604.01074
Abstract
Despite the proven advantages of scenario-based stochastic model predictive control for the operational control of water networks, its applicability is limited by its considerable computational footprint. In this paper we fully exploit the structure of these problems and solve them using a proximal gradient algorithm parallelizing the involved operations. The proposed methodology is applied and validated on a case study: the water network of the city of Barcelona.
| Item Type: | Working Paper (Working Paper) |
|---|---|
| Identification Number: | arXiv:1604.01074 |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Research Area: | Computer Science and Applications |
| Depositing User: | Caterina Tangheroni |
| Date Deposited: | 04 Oct 2016 08:44 |
| Last Modified: | 04 Oct 2016 08:44 |
| URI: | http://eprints.imtlucca.it/id/eprint/3544 |
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- GPU-accelerated stochastic predictive control of drinking water networks. (deposited 04 Oct 2016 08:44) [Currently Displayed]
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