Artificial Intelligence in Control
A special issue of Computers (ISSN 2073-431X).
Deadline for manuscript submissions: 30 September 2025 | Viewed by 10129
Special Issue Editors
Interests: deep learning; optimal control; magnetic resonance imaging; pulse design
Interests: diffusion MRI; machine learning; mathematical modelling
Special Issue Information
Dear Colleagues,
Dynamic systems that can be controlled by humans or computers (or by a combination) exist in many situations ranging from, e.g., transportation, fabrication, and trade to medical imaging, engineering, and physics experiments. Depending on the application, control decisions typically depend on the dynamic system state, its objective, and variable external conditions, but also on control and state limits, and various costs. This is typically gathered in an overall performance/cost functional or an optimization problem, and then optimized with optimal control or other optimizers by computers. Depending on the performance ambition and the amount of information in play, the optimization problem can easily grow and become impractical, especially if the result is needed in real time, e.g., for autonomous cars, if external conditions may rapidly change, or in specialized situations tailored to hospital patients in for treatment, etc. In such cases, conventional optimization methods may not meet our expectations. Artificial intelligence has already proven useful and a potential candidate to steer some control systems, and it certainly solves many other tasks we hand to computers. This Special Issue welcomes original research and review articles on all aspects of artificial intelligence in control systems. Topics of interest include but are not limited to the following areas:
- Medical imaging and treatment
- (Quantum) optimal control
- Control systems (PID, fuzzy logic, etc.).
Dr. Mads Sloth Vinding
Dr. Ivan Maximov
Dr. Christoph Stefan Aigner
Guest Editors
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Keywords
- deep learning
- neural networks
- artificial intelligence
- (quantum) optimal control
- (nuclear) magnetic resonance (imaging)
- medical imaging
- controls systems
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