Emerging Model-Based and Data-Driven Techniques in Control, Communication and Learning
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: closed (30 June 2022) | Viewed by 2032
Special Issue Editors
Interests: control; optimization; machine learning; intelligent transportation systems; power systems
Interests: reinforcement learning for control; neural networks
Interests: stochastic systems; system identification; intelligent systems; fault-tolerant control; machine learning; robotics
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; mobile and satellite communication; optimization and control
Interests: model predictive control; reinforcement learning; connected and automated vehicles; electric vehicles; renewable energy systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue aims at encouraging the discussion and collaboration of researchers in the fields of control, communication, and learning. Traditional techniques in these fields usually rely on system modeling. However, as the models of certain engineering systems become more complex, it is becoming harder, near impossible even, to build a suitable model. In the last two decades, thanks to the dramatic development of data-driven technologies, a promising possibility has been provided in terms of dealing with control, communication, and learning problems using either online or offline data. This Special Issue invites submissions on all topics regarding theory and applications in control, communication, and learning, including but not limited to the following topics described in the keywords.
Dr. Weinan Gao
Dr. Yongliang Yang
Dr. Vladimir Stojanovic
Dr. Di Zhang
Dr. Jun Chen
Guest Editors
Manuscript Submission Information
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Keywords
- Data-driven study in transportation and driving simulation
- Data-driven and model-based controller design
- Applications of data mining and machine learning
- Path planning, control, and actuation of robots
- Data-driven and model-based wireless communication
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