POSTDOC POSITION ON ROBUST OPTIMAL FEEDBACK CONTROL DESIGN METHODOLOGIES FOR MULTIVARIATE MECHATRONIC SYSTEMS

04 July 2018

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Interested?

Please use the online application tool to submit your application and include: (i) an academic CV with photo, (ii) a pdf of your diplomas and transcript of course work and grades, (iii) a list and pdf files of your publications, (iv) a statement of research interests and career goals (max. 2 pages), (v) contact details of at least two referees. Note that the positions might be filled in earlier if an excellent candidate is found. For more information please contact Prof. dr. ir. Jan Swevers, tel.: +32 16 32 25 40, mail: jan.swevers@kuleuven.be or Prof. dr. ir. Goele Pipeleers, tel.: +32 16 37 26 94, mail: goele.pipeleers@kuleuven.be.

You can apply for this job no later than August 31, 2018 via the online application tool
KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.

Apply before 31 August 2018

The research will take place in the MECO (Motion Estimation Control and Optimization) research team of the Department Mechanical Engineering of KU Leuven. The MECO research team focusses on modelling, estimation, identification, analysis and optimal control of motion and motion systems such as mechatronic systems or machine tools. It combines theoretical contributions (development of design methodologies) with experimental knowhow (implementation and experimental validation on lab-scale as well as industrial setups). The theoretical research benefits from the group’s expertise on numerical optimization, especially convex optimization. MECO is member of Flanders Make - the strategic research center for the manufacturing industry.

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Responsibilities

This research project is set up to address the strong demand from the industry for control design software that can adequately cope with the complex behavior of multivariate systems and optimize the control configuration, that is, the combination of sensors, actuators, and the control architecture. More complicated controllers and additional sensors and actuators not necessarily lead to an economic profit. The balance between the enhanced performance and robustness and the elevated costs (more sensors and actuators, and a more complex control architecture) must be right. Hence, when considering a more complicated control configuration, a systematic analysis and optimization of this interplay must be performed.

In this research project you will contribute to (1) methodologies and software to design robust optimal controllers for multivariate linear and linear parameter varying systems, (2) methodologies and software for the optimization of control configurations, (3) a user-friendly design interface for (1) and (2), and (4) the application and evaluation of robust optimal controllers on multivariate mechatronic setups with high industrial relevance. This includes experimental identification of the setups, implementation of controllers, comparison of control configurations of different complexity and comparison with decoupled PID-like control approaches.

You will work in close collaboration with two PhD researchers that are doing a PhD on the abovementioned topics.

Profile

An ideal candidate has a PhD degree in engineering (mechanical, control ...) or mathematics and a strong background in development and application of robust control design methodologies, numerical optimization, programming (Matlab, C/C++), has an interest in work on real-world experiments, and is a team player. Proficiency in English is a requirement.

Offer

A fully funded postdoctoral position in an international context for one year at KU Leuven (renewable); a start date in course of 2018 is to be agreed upon.

KU Leuven is among the top European universities and a hub for interdisciplinary research in the fields of systems, control and optimization.