Master Thesis Autonomous Agentic Control Design - Translating System-Theoretic Properties into Self-Improving Synthesis Loops

Aufgaben

Control engineering is transitioning. While traditional design relies on manual selection and calibration, agentic coding and self-improving software loops enable a new paradigm. The primary engineering bottleneck is shifting from developing a specific control algorithm to orchestrating an autonomous system that can discover, synthesize and tune the optimal controller for any plant.

Your thesis explores how autonomous meta-agents can automate this end-to-end design process for complex controllers. The core objective is to translate modern control theory into structured, automated steps. Rather than relying on trial-and-error code generation, the agent must analyze critical requirements, such as constraint satisfaction, state limitations and safety boundaries, to make methodologically grounded decisions.

You will design a reasoning framework that will guide the agent in selecting and synthesizing advanced control architectures. This framework should balance nonlinear methods (e.g., exact linearization, backstepping and sliding mode) with optimization-based approaches, such as model predictive control and reinforcement learning.

Practically, you will build a closed-loop simulation framework where the agent interacts with physical benchmarks using Python-based control and learning libraries. The agent will iteratively write control code, run simulations and programmatically verify safety and performance before deployment.

This project offers a unique opportunity to work at the direct intersection of generative AI and safety-critical control systems, developing a verifiable system that combines AI adaptability with rigorous engineering guarantees.

Profil

• Education: Master studies in the field of Cybernetics, Engineering, Mathematics, Computer Science or comparable
• Experience and Knowledge: profound knowledge of control engineering and machine learning; experience with Python and agentic AI
• Personality and Working Practice: you are a person with an autonomous, systematic working practice and analytic thinking
• Work Routine: partially mobile working is possible
• Languages: very good in English

Wissenswertes zum Job

• Start: according to prior agreement
• Duration: 6 months

Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.