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The PhD position is part of the European Training Network ‟ELO-X – Embedded Learning and Optimisation for the neXt generation of smart industrial control systems”.
ELO-X will recruit altogether 15 PhD fellows at six research universities and five international companies from five European countries, who will meet regularly during exchange visits, training events, workshops, and summer schools organized by the network. The position at KU Leuven is focused on producing performant formulations of optimal control problems for a range of robotics applications. The position is based in the MECO research team headed by prof. Jan Swevers. The aim is the development of open-source software implementations of tailored model predictive control schemes with a strong industrial relevance. There will be a close cooperation with the other ELO-X PhD fellows, in particular with those partners that will host mutual exchange visits of several months durations: at École Polytechnique Fédéral de Lausanne and ShangaiTech, the connection with generic methodological advances in the field of computational control and mathematical optimisation will be strengthend, while at Atlas Copco, an industrial perspective will be deepened.BACKGROUNDDigital technologies are transforming all sectors of our economy and will increasingly do so in the years to come. Thanks to the increasing capabilities of digital technologies, the next generation of smart industrial control systems (SICS) are expected to learn from streams of data and to take optimal decisions in real-time on the process at hand, leading to increased performance, safety, energy efficiency, and ultimately value creation. Numerical optimisation is at the very core of both learning and decision making, since both the extraction of information from data and the choice of the most suitable action are naturally cast as optimisation problems and solved numerically. However, to realize this potential embedded learning and optimisation methods needs to be developed, able to operate in industrial devices and to guarantee high safety standards. ELO-X addresses the timely and pressing need for highly qualified and competent researchers, able to develop embedded learning- and optimisation-based control methodologies for SICS, thus enabling new technologies and the next generation of digital industrial products and processes.The applicant will be embedded in the MECO (Motion Estimation Control and Optimisation) research team of the KU Leuven Department Mechanical Engineering. The MECO team focusses on the identification, analysis and control of mechatronic systems such as autonomous guided vehicles, robots, and machine tools. It combines theoretical innovations with experimental validations. The theoretical research benefits from the team’s expertise on numerical optimisation, while MECO’s practical knowhow and industrial collaboration are supported by its participation in Flanders Make – the Flemish strategic research centre for the manufacturing industry.The group has a strong history in open-source research codes such as CasADi, Rockit, LCToolbox, and ROFALT.The applicant will further be embedded in the ELO-X ecosystem which encompasses leading experts in mathematical modelling and optimisation-based control and estimation and shall prepare the fellows for a high-level career in advanced control engineering in industry or in academia
PhD Project: MPC for flexible robotic systems: The European manufacturing industry is trending towards the production of highly-customized complex products in small quantities, for which a flexible production system is key to be cost-effective. Flexible automation demands robotic systems such as mobile platforms and serial manipulators to perform multiple and highly complex tasks in unstructured and uncertain environments, hereby involving extensive sensing such as vision and force, and learning on-the-spot through active sensing. MPC holds great potential for controlling such systems since they are characterized by highly nonlinear and coupled dynamics as well as hard operational constraints.
The overall goal of this project is to develop optimisation-based control approaches that increase the performance and flexibility of robotic systems. The first objective is to develop appropriate robot models and tailored embedded optimisation algorithms that are capable of solving the highly nonlinear optimisation problems arising in robotics MPC at a rate in the range of 100-1000 Hertz.The second objective is to effectively deal with uncertainties: MPC will be merged with active-sensing strategies to learn properties of the environment and reduce uncertainty in the environment while executing the task, and augmented with risk-averse policies to handle the remaining uncertainty. The third objective is to embed the control algorithms in an automated tool chain that facilitates the robot (re)programming for different tasks. In flexible automation, the programming effort is a major cost factor and it is decisive to the economic viability of a robot application.
SUPERVISORS AND MAIN CONTACTSSupervising team at KU Leuven: prof. Jan Swevers (head of the MECO research group), prof. Goele Pipeleers (control, numerical optimisation), Dr. Joris Gillis (nonlinear optimisation, optimal control and model predictive control)Main Contacts at the ELO-X Partner Institutes which could host secondments: École Polytechnique Fédéral de Lausanne: prof. Colin Jones; Atlas Copco: Dr. Kasper Masschaele; ShanghaiTech: prof. Boris Houska
Ideal candidates hold a Master’s degree in engineering, computer science, or applied mathematics. Successful candidates are typically ranked at or near the top of their classes (obtained at least a distinction), have a solid background in systems and control, robotics, optimisation, relevant computer programming skills (Python or Matlab, C++), and enthusiasm for scientific research, including real-hardware implementations and experiments. Team player mentality, independence, and problem solving attitude are expected, and proficiency in English is a requirement.Applicants whose mother tongue is not English must present an official language test report. The acceptable tests are TOEFL, IELTS, and Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Required minimum scores are: • TOEFL: 600 (paper-based test), 100 (internet-based test); • IELTS: 7 (only Academic IELTS test accepted);
MARIE CURIE ELIGIBILITY CRITERIA IN SHORTTo be eligible, you need to be an "early stage researcher" i.e. simultaneously fulfil the following criteria at the time of recruitment:a) Nationality: you may be of any nationality.b) Mobility: you must not have resided or carried out your main activity (work, studies, etc...) in Belgium for more than twelve months in the three years immediately prior to your recruitment under the ELO-X project. c) Qualifications and research experience: you must be in the first four years of your research career after the master degree was awarded.
Timeline and renumeration: The ideal start time is in early summer 2021. The PhD project lasts for the duration of four years, and is mainly carried out at KU Leuven. The PhD years include international seasonal schools and three longer visits – so called ”secondments” – of two months at other groups in the ELO-X network, depending on the project needs and the scientific interests of the PhD fellows. Three years are funded by the ELO-X project, with a fourth year funded by KU Leuven. The remuneration is generous and will be in line with the EC rules for Marie Curie grant holders. It consists of a salary augmented by a mobility allowance, resulting in a net monthly income of about 2100-2300 Euro depending on family status.