Data-Driven Optimization Control of Intelligent Systems

Dear Colleagues,

Nowadays, with the development of science and technology, intelligent systems a key role in industrial applications. As systems become increasingly complex, it is difficult to accurately characterize the true state of the system using models. To more accurately depict the true state of the system, existing data can be used to approximate the true state of the system, and data-driven methods are increasingly attracting widespread attention. Meanwhile, with the development of optimization control theory, data-driven optimization control has become increasingly important in the performance analysis of intelligent systems. This Special Issue covers the following topics: data-driven theory, optimization, control, estimation, reinforcement learning, and intelligent systems.

This Special Issue will address modern challenges in data-driven methods, optimization methods, control methods, and their relationships to systems. By bridging data-driven methods, optimization methods, and control methods, it paves the way for designing more effective decision-making algorithms for intelligent systems. Original and innovative research studies from both academia and industry are welcome.

Dr. Guoqiang Tan
Dr. Ting Wang
Guest Editors

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