Abstract
Modern intelligent control theory has experienced multi-stage development from classical control to fuzzy control, neural networks, and model predictive control, which not only improves the flexibility and adaptability of control systems but also promotes interdisciplinary research. With the advancement of science and technology and social development, intelligent control theory will be further combined with machine learning, big data, and other fields in the future to promote industrial automation and technological innovation. This article reviews the development history of modern intelligent control theory, its main theories, and its applications in robot manufacturing, power electronics, and other fields. It also discusses the current challenges and future development trends in the field of intelligent control.
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