LLM-Enabled Cyber-Physical Systems: Survey, Research Opportunities, and Challenges

Cyber-Physical Systems (CPS) integrate computational elements with physical processes via sensors and actuators. While CPS is expected to have human-level intelligence, traditional machine learning which is trained on specific and isolated datasets seems insufficient to meet such expectation. In recent years, Large Language Models (LLMs), like GPT-4, have experienced explosive growth and show significant improvement in reasoning and language comprehension capabilities which promotes LLM -enabled CPS. In this paper, we present a comprehensive review of these studies about LLM -enabled CPS. First, we overview LLM-enabled CPS and the roles that LLM plays in CPS. Second, we categorize existing works in terms of the application domain and discuss their key contributions. Third, we present commonly-used metrics and benchmarks for LLM -enabled CPS evaluation. Finally, we discuss future research opportunities and corresponding challenges of LLM -enabled CPS.