mlsanityData to 14 Oct 2026

LLM-Agent-Controller: A Universal Multi-Agent Large Language Model System as a Control Engineer

arXiv 2505.19567 ↗First posted 26 May 2025cs.AI cs.MAcited by 5

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

This study presents the LLM-Agent-Controller, a multi-agent large language model (LLM) system developed to address a wide range of problems in control engineering (Control Theory). The system integrates a central controller agent with multiple specialized auxiliary agents, responsible for tasks such as controller design, model representation, control analysis, time-domain response, and simulation. A supervisor oversees high-level decision-making and workflow coordination, enhancing the system's reliability and efficiency. The LLM-Agent-Controller incorporates advanced capabilities, including Retrieval-Augmented Generation (RAG), Chain-of-Thought reasoning, self-criticism and correction, efficient memory handling, and user-friendly natural language communication. It is designed to function without requiring users to have prior knowledge of Control Theory, enabling them to input problems in plain language and receive complete, real-time solutions. To evaluate the system, we propose new performance metrics assessing both individual agents and the system as a whole. We test five categories of Control Theory problems and benchmark performance across three advanced LLMs. Additionally, we conduct a comprehensive qualitative conversational analysis covering all key services. Results show that the LLM-Agent-Controller successfully solved 83% of general tasks, with individual agents achieving an average success rate of 87%. Performance improved with more advanced LLMs. This research demonstrates the potential of multi-agent LLM architectures to solve complex, domain-specific problems. By integrating specialized agents, supervisory control, and advanced reasoning, the LLM-Agent-Controller offers a scalable, robust, and accessible solution framework that can be extended to various technical domains.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 24 of its 30 references that are in the map. First posted on arXiv 26 May 2025.

Builds on

24 of 30 references.

Closest ancestors · 4

Same direction, newest first

  1. 2024ControlAgent: Automating Control System Design via Novel Integration of LLM Agents and Domain Expertise17 Oct
  2. 2024Large Language Model based Multi-Agents: A Survey of Progress and Challenges21 Jan
  3. 2024Small LLMs Are Weak Tool Learners: A Multi-LLM Agent14 Jan
  4. 2023A Survey on Large Language Model based Autonomous Agents22 Aug

Other references · 20

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  4. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  5. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  6. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,211
  7. 2023Large Language Models as Tool Makerscited by 303
  8. 2024Data Interpreter: An LLM Agent For Data Sciencecited by 225
  9. 2023Large Language Model Guided Tree-of-Thoughtcited by 221
  10. 2024EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instructioncited by 154
  11. 2024FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Makingcited by 113
  12. 2024AgentReview: Exploring Peer Review Dynamics with LLM Agentscited by 93
8 more
  1. 2024Self-Organized Agents: A LLM Multi-Agent Framework toward Ultra Large-Scale Code Generation and Optimizationcited by 84
  2. 2023MechAgents: Large language model multi-agent collaborations can solve mechanics problems, generate new data, and integrate knowledgecited by 63
  3. 2025LLM Agents Making Agent Toolscited by 48
  4. 2024LAVE: LLM-Powered Agent Assistance and Language Augmentation for Video Editingcited by 47
  5. 2024Capabilities of Large Language Models in Control Engineering: A Benchmark Study on GPT-4, Claude 3 Opus, and Gemini 1.0 Ultracited by 37
  6. 2024Large Language Model Agent as a Mechanical Designercited by 21
  7. 2024Toward LLM-Agent-Based Modeling of Transportation Systems: A Conceptual Frameworkcited by 19
  8. 2024Constructing Mechanical Design Agent Based on Large Language Modelscited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.

  1. 2025The Era of Agentic Organization: Learning to Organize with Language Modelscited by 7
  2. 2026PrismAgent: Illuminating Harm in Memes via a Zero-Shot Interpretable Multi-Agent Frameworkcited by 0
  3. 2026Benchmarking and Reasoning Distillation of Large Language Models for Feedback Controller Design in Complex Dynamical Systemscited by 0
  4. 2026Large Language Models in the Loop: A Stability- and Network-Aware Survey in Networked Control, Cyber-Physical, and Multi-Agent Systemscited by 0
  5. 2026A Scalable Trust Discovery Architecture for the Internet of Agentscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Large Language Model Agent: A Survey on Methodology, Applications and Challenges
  2. 2024Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects
  3. 2025From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Users
  4. 2025LLMs Working in Harmony: A Survey on the Technological Aspects of Building Effective LLM-Based Multi Agent Systems
  5. 2025LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey
  6. 2024Practical Considerations for Agentic LLM Systems
  7. 2023The Rise and Potential of Large Language Model Based Agents: A Survey
  8. 2024A Survey on LLM-based Multi-Agent System: Recent Advances and New Frontiers in Application