PhD Position for Learning-Based Model Predictive Control with Formal Guarantees

14.05.2023, Wissenschaftliches Personal

The research group Cyber-Physical Systems of Prof. Matthias Althoff at the Technical University of Munich offers a PhD position in the area of learning-based model predictive control with formal guarantees. The Technical University of Munich is one of the top research universities in Europe fostering a strong entrepreneurial spirit and international culture.

Expected Starting Date: 01 August 2023-01 December 2023

Closing Date for Applicants: 15 July 2023

Duration: 3 years with a possible extension

Project and Job Description

Cyber-physical systems are complex systems that combine physical capabilities with computational capabilities. These include medical devices and systems, process controls, autonomous vehicles, avionic systems, energy systems, robots, manufacturing systems, and smart structures. The increasingly complex requirements of cyber-physical systems makes it very difficult to control them or even prove that their specification is met. For this reason, learning-based model predictive control is an active area of research. However, this approach is not yet scalable and formally correct for arbitrary nonlinear systems.

To address this problem, we propose a novel approach that combines machine learning, optimization techniques, and reachability analysis. We will use machine learning twofold: to identify the uncertain system dynamics during operation and to support classical optimization techniques in finding global minima. Optimization techniques will be primarily used to realize model predictive control based on the learned system dynamics. Finally, we utilize reachability analysis to ensure the safety of the system despite sensor noise, disturbances, and model uncertainties.

Among other use cases, we will evaluate our approach on our autonomous vehicle EDGAR. All developed algorithms will be available through our software tools CORA (cora.in.tum.de ) for reachability analysis and AROC (aroc.cps.in.tum.de ) for formal controller synthesis.

Previous Work

https://mediatum.ub.tum.de/doc/1524264/205786.pdf
https://mediatum.ub.tum.de/doc/1454141/411080880765.pdf
https://arxiv.org/abs/2210.10691

Job Specifications

• Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically mathematics, physics).
• Fluency in spoken and written English is required.
• Good programming skills in at least one programming language, e.g. MATLAB, C/C++, Python.
• Highly motivated and keen on working in an international and interdisciplinary team.
• Applicants with strong background in the following fields are preferred:
  • Control Theory
  • Optimization
  • Formal methods
  • Robotics

Context

The applicant will be directly advised by Prof. Matthias Althoff (https://www.ce.cit.tum.de/air/people/prof-dr-ing-matthias-althoff ). Besides excellent skills for conducting innovative science, the candidate should also be talented in implementing research results. The candidate will be integrated in a supportive research environment.

Our Offer

PhD remuneration will be in line with the current German collective pay agreement TV-L E13 (around 4500 Euros/month). Technical University of Munich is an equal opportunity employer committed to excellence through diversity. We explicitly encourage women to apply. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Contact

International candidates are highly encouraged to apply. Please submit your complete application (in English or German) via our application form: https://wiki.tum.de/display/cpsforms/Ph.D.+Application . Fill out all mandatory fields (*) and kindly use “Learning-Based Model Predictive Control with Formal Guarantees” as the “Title of Position”. Please do not include a cover letter.
Further similar job offerings will be announced on https://www.ce.cit.tum.de/en/air/open-positions/scientific-staff/ .

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: Lukas Schäfer ([email protected])