Review investigates AI-driven intelligent control evolution and technologies, highlighting implications for future advancements.
Key Points
This paper reviews the evolution and key technologies of AI-driven intelligent control systems, assessing their theoretical and practical advancements.
Systematic review of paradigm evolution divided into knowledge-based, data-based, and knowledge-data-fused control.
In-depth analysis of theoretical frameworks and progress in key technologies.
Evaluation of practical applications in industrial automation, unmanned systems, power systems, and process control.
Identified three stages of intelligent control paradigm evolution: knowledge-based, data-based, and fused approaches.
Highlighted key technologies such as deep reinforcement learning and multi-model intelligent control.
Envisioned future directions for intelligent control, focusing on human-machine hybrid systems and generative AI integration.