Data-driven control and learning has been developed quickly both in theory and applications recently. The deep involvement of information science in practical processes poses enormous challenges to the existing control science and engineering due to their size, distributed nature and complexity. Modeling these processes accurately using first principles or identification is almost impossible although these plants produce huge amount of operation data in every moment. The high-tech hardware/software and the cloud computing enable us to perform complex real-time computation, which makes implementation of data-driven control and method for these complex practical plants possible. It would be very significant if we can learn the systems' behaviors, discover the relationship of system variables by making full use of on-line or off-line process data, to directly design controller, predict and assess system states, make decisions, perform real-time optimization and conduct fault diagnosis.
Sponsor Type:3; 9; 9
The English papers accepted by our previous DDCLS conferences had been included in the IEEE Xplore, and indexed by EI Compendex or ISTP database. The DDCLS’23 covers both theory and applications in all the areas of data driven control and learning systems. The topics of interest include, but are not limited to:
05月12日
2023
05月14日
2023
初稿截稿日期
初稿录用通知日期
终稿截稿日期
注册截止日期
2024年05月17日 中国 Kaifeng
2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS)2022年05月13日 中国 Chengdu
2022 IEEE 11th Data Driven Control and Learning Systems Conference2021年05月14日 中国 Suzhou
2021 IEEE 10th Data Driven Control and Learning Systems Conference2019年05月24日 中国
2019 IEEE 8th Data Driven Control and Learning Systems Conference2018年05月25日 中国
2018 IEEE 7th Data Driven Control and Learning Systems Conference2017年05月26日 中国 Chongqing,China
2017 6th Data Driven Control and Learning Systems2017年05月26日 中国 Chongqing,China
The 6th Data Driven Control and Learning Systems Conference
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