System identification, modeling and control algorithms have always been the core issues of control theory. With the improvement of the requirements for system cognition, interpretability and modeling accuracy, the traditional system modeling technologies have certain limitations and defects. In recent years, due to the progress of science and technology and the development of artificial intelligence, system modeling and control has ushered in a new opportunity. Entropy and information-theoretic concepts also have strong relevance to intelligent modeling and control, such as the use of entropy to calculate the information entropy of data sets and to describe the stability of the system. Innovative intelligent algorithms, advanced system modeling strategies and practical control methods are urgently needed.
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