Theoretical Approaches, Practical Applications and Development Trends of Intelligent Control

The advent of Industry 4.0 and the Internet of Things (IoT) has led to a surge in system complexity, propelling the development of intelligent control systems that exhibit autonomy and adaptivity. These systems have found widespread application in diverse domains, including industry, transportation, and healthcare. The present study focuses on three mainstream methods of intelligent control: fuzzy logic control, neural network control, and reinforcement control. In addition to a review of the latest research in this field from the past five years, the study also examines the latest application areas of current expansion. In light of the prevailing trends in the domain of intelligent control, a rational analysis has been conducted to assess the technical, ethical, and practical limitations and challenges pertinent to this field. This analysis has led to the conclusion that intelligent control systems are poised to evolve towards higher degrees of autonomy, safety, and sustainability in the future.