AI 中文总结
本文提出首个LLM驱动的智能体系统AI控制科学家，通过任务建模、控制器设计、参数调优三个智能体自动生成优化控制器，性能优于现有基线，有望推动控制系统设计从人类驱动转向智能体驱动。
AI 中文摘要
控制系统设计对现代工业至关重要，例如化工过程温度调节和航空发动机控制。然而，传统控制设计工作流程严重依赖专家知识和大量手动参数调优，导致效率和可扩展性有限。为此，本文提出AI控制科学家（AICS），这是首个大语言模型（LLM）驱动的智能体，能够根据语言设计需求自动生成优化的控制器。具体而言，任务建模智能体将用户需求解释为工程约束；控制器设计智能体生成候选控制器结构和可执行代码；参数调优智能体根据闭环性能准则优化控制器参数。实验表明，所提出的智能体系统可自动生成多种代表性控制系统，在设计成功率和优化效率上均优于现有自动化基线。该研究有望将控制系统设计从人类驱动转变为智能体驱动，为模型预测控制及其他先进控制系统设计铺平道路。
英文摘要
Control system design is critical for modern industry, such as chemical process temperature regulation and aero-engine control. However,traditional control design workflows rely heavily on expert knowledge and extensive manual parameter tuning, resulting in limited efficiency and scalability. To this end, this paper proposes AI Control Scientist (AICS), the first large language model (LLM)-driven agent capable of automatically generating optimized controller from language design requirements. Specifically, a Task Modeling Agent interprets user requirements to engineering constraints; a Controller Design Agent generate candidate controller structures and executable code; and a Parameter Tuning Agent refine controller parameters under closed-loop performance criteria. Experiments demonstrate that the proposed agentic system can automatically generate multiple representative control systems, outperforms existing automated baselines in both design success rate and optimization efficiency. This work has the potential to transform control system design from human-driven to agent-driven, paving the way for model predictive control and other advanced control systems design.
