PhD Position for Model Predictive Control with Formal Guarantees

04.03.2023, 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 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 May 2023-01 October 2023

Closing Date for Applicants: 15 April 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, model predictive control with formal guarantees is an active area of research. However, there exist no scalable and formally correct synthesis methods for arbitrary nonlinear systems whose algorithmic parameters are automatically tuned.

To address this problem, we propose a synthesis approach that does not rely on any discretization and instead uses optimization techniques in combination with reachability analysis. We plan to translate temporal logic specifications into hybrid automata and compute the product automaton with the system to be controlled. This way, the model predictive control problem can be reformulated as reach-avoid problems for constrained and disturbed hybrid systems. Through optimization, we will obtain an optimal nominal solution and ensure that all other solutions originating from uncertain initial states, disturbances, and sensor noise also meet all constraints.

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

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 and preference will be given to disabled applicants with equivalent qualifications.

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 “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/ .

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Kontakt: [email protected]