The position is already taken.
Funding: TEMPO (EU FP7) -- Marie Curie Initial Training Network (ITN) on Training in Embedded Predictive Control and Optimization (ESR 12).
Duration: 3 years starting from February 2014.
Financial terms: 2500 EUR as a monthly gross salary with additional 680 EUR per month to cover expenses linked to the personal household, relocation and travel expenses of the researcher.
Hosting institution: Slovak University of Technology in Bratislava, Slovakia.
Objectives: The early-stage researcher (ESR) will be trained in novel methods for optimization-based control on Programmable Logic Controllers (PLCs). Since PLCs typically provide very limited memory resources on the scale of several kilobytes, the optimization strategy has to be suitably simplified.
Planned secondments: 4 months with ETH/ABB, Zurich, Switzerland for work on combination of on-line and off-line optimization, and case study, 2 months at the Imperial College, London, UK for studies on comparisons between PLCs and FPGAs.
Note that knowledge of the Slovak language is not required. The working language in our group is English. Applicants are recommended to demonstrate that they possess the above mentioned requirements by citing concrete evidence and examples in their application. Outstanding students with only a partial match to this list are encouraged to apply.
The position adheres to the European and the beneficiaries policy of balanced ethnicity, age and gender. It is an objective to increase the number of females in scientific positions. Female applicants are therefore encouraged to apply.
How to apply: Applicants are required to submit following documents by email to firstname.lastname@example.org:
Eligibility: At the time of recruitment, the researcher must not have resided or carried out his/her main activity (work, studies, etc) in Slovakia for more than 12 months in the 3 years immediately prior to his/her recruitment under the project. Compulsory national service and/or short stays such as holidays are not taken into account.
Tasks and methodology: The training will be devoted to new methods and algorithms aimed at reducing memory footprints of Explicit Model Predictive Control (MPC) strategies by either synthesizing suboptimal feedbacks or optimal control laws of low complexity. The main challenge for the ESR will be to devise control strategies of minimal complexity while maintaining theoretic guarantees of stability, feasibility, and optimality. Special emphasis will be put on implementation of Embedded MPC controllers on PLCs by using standardized programming tools, like Ladder logic and Statement list.
Plan of work: Literature review of existing methods for implementation of optimization-based controllers on PLCs, selection of experimental benchmarks, identification of mathematical models, synthesis of MPC policies for benchmark applications, development of novel methods for complexity reduction, implementation of developed methods in form of an easy-to-use tool, implementation of low-complexity MPC controllers on PLCs, development of a unified tool for export of MPC controllers to PLC code, validation of experimental results.
Expected results: Report on available simplification techniques, progress report, code-generation platform for export of Embedded MPC into native PLC code, software tool for simplification of control laws, experimental verification of results in laboratory conditions.
Dissemination: At least two publications in leading peer-reviewed journals; At least four publications in leading international peer-reviewed conferences.