An agentic LLM framework with multi-agent workflow, digital process plant twin, and Graph RAG on CPSMod ontology generates and validates fault recovery actions in simulation for discrete batch and continuous stirred-tank processes.
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A tutorial framework for knowledge-grounded LLM agents as constrained planners for fault recovery in process plants, including validation strategies and open Python environments for two case studies.
A semantic framework uses a knowledge graph on modular alignment ontology plus constrained LLM to generate C&E logic, narratives, and SWRL rules, shown on a modular process plant with claimed reduction in manual effort.
citing papers explorer
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From Detection to Action: Using LLM Agents for Fault-Tolerant Control
An agentic LLM framework with multi-agent workflow, digital process plant twin, and Graph RAG on CPSMod ontology generates and validates fault recovery actions in simulation for discrete batch and continuous stirred-tank processes.
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A Tutorial on Autonomous Fault-Tolerant Control Using Knowledge-Grounded LLM Agents
A tutorial framework for knowledge-grounded LLM agents as constrained planners for fault recovery in process plants, including validation strategies and open Python environments for two case studies.
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Automating Cause-Effect Specification with Knowledge Graphs and Large Language Models
A semantic framework uses a knowledge graph on modular alignment ontology plus constrained LLM to generate C&E logic, narratives, and SWRL rules, shown on a modular process plant with claimed reduction in manual effort.