Explore/agent app/AI Control Scientist: LLM-driven Agentic System for Automated Control Design
A

Haiteng Wang, Weihao Li, Jing Zhang, Lei Ren/AI Control Scientist: LLM-driven Agentic System for Automated Control DesignUnknown

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.

agent app
GitHubCompare
Refreshed 1mo ago
OverviewActivity52wAlternativesDocs
Stars0
Forks0
HF Downloads—30d
Last commit—
Refreshed1mo ago
Project healthUnknownNo activity data.
Production readinessResearch / EarlyBest for exploration and prototyping.
Risk notesUnknown licenseVerify license before production use.
AgentHub Score
55 / 100
Composite score from 6 signals. How we score →
Active project
55Score
Growth
40C
Activity
30C
Documentation
70C+
Maturity
45C
Community
42C
Production
58C
GitHub stars · 44 days observed0 not enough history
snapshots
Repository activity · 44 days observedReal snapshots from pushed_at
inactivepushed
2026-08-292026-10-13
Practical assessment
Should you use it?

✓ Best for

  • Research and experimentation
  • Prototype development
  • Learning agentic patterns

◎ Strengths

  • Active community
  • Open source
  • Well-documented API

✕ Not ideal for

  • Untested at scale without validation
  • Teams without AI/ML expertise

⚠ Watch-outs

  • Review changelog before updating
  • Verify license for commercial use
Technical details
What's inside
Language—
License—
Sourcearxiv
Open source✗ No
Commercial use—
Docs—
Demo—

AgentHub Score

55
Score 55/100
Below average

Alternatives

C
ClinAgent: A ReAct-Based Agent for Conversational Access to Clinical Trial Information
0 · agent app
55
A
Agent2UCB: Agentic System for Generative Engine Optimization
0 · agent app
55
A
Agentic AI for Scientific Reasoning in Autonomous Quantum Sensing Experiments
0 · agent app
55
I
IDP AutoOpt: Agent-Driven Optimization of Document Processing Pipeline Configurations
0 · agent app
55Compare all →

Recent activity

Latest commit ——
Indexed by AgentHub crawler1mo ago
Monitor for new releasesongoing