Results
| Title: | IoT-Enabled Motion Control: Architectural Design Challenges and Solutions | Authors: | Lesi, Vuk; Jakovljević, Živana   ; Pajić, Miroslav |
Issue Date: | 2023 | Publication: | IEEE Transactions on Industrial Informatics | ISSN: | 1551-3203 IEEE Transactions on Industrial Informatics Search Idenfier |
Type: | Article | Collation: | vol. 19 br. 3 str. 2284-2294 | DOI: | 10.1109/TII.2022.3202175 | WoS-ID: | 000966119700001 | Scopus-ID: | 2-s2.0-85137911973 | URI: | https://enauka.gov.rs/handle/123456789/604755 https://machinery.mas.bg.ac.rs/handle/123456789/5616 |
Project: | MISSION4.0 - Deep Machine Learning and Swarm Intelligence-Based Optimization Algorithms for Control and Scheduling of Cyber-Physical Systems in Industry 4.0 Ministarstvo prosvete, nauke i tehnološkog razvoja Republike Srbije, Ugovor br. 200105 (Univerzitet u Beogradu, Mašinski fakultet) ONR (Grant Number: N00014-17-1-2504 and N00014-17-1-2012) NSF (Grant Number: CNS-1652544) |
M-category: | 21a+M21a+ |
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