The aim of this phd project is to develop, implement and
experimentally validate efficient numerical solution methods for optimizing in real-time the motion of machine tools and robot manipulators.
Both open- and closed-loop methods are considered. The former methods generate
optimal motion trajectories on-line, which are then given to the lower level
controller; the closed-loop methods are fast MPC algorithms. For both types
of control problems, optimality with respect to execution time, energy, dynamic
machine loading and residual vibrations will be investigated, taking into account
system constraints such as actuator saturation, maximal velocity and acceleration.
The main challenge is the high sampling rate, in the range of kHz, at which the
embedded optimization problems must be solved. Different problem classes can be
defined according to complexity of the considered system and degree of desired
motion accuracy and robustness: linear time invariant systems, linear parameter
varying systems, nonlinear dynamic (robot) systems, considering parameter
uncertainty and tracking accuracy tolerances. The developed optimal control
algorithms will be implemented and experimentally validated on an industrial
pick-and-place machine and robot manipulator.
This research project is a continuation of the research described on:
Besides a competitive salary we offer a stimulating research environment within
our division PMA (http://www.mech.kuleuven.be/pma/) and the Optimization in
Engineering Center OPTEC(http://www.kuleuven.be/optec/). This phd project will
be supervised by Prof. Jan Swevers, and Prof. Moritz Diehl.
The requirements are a strong background in control and dynamic system modeling, numerical optimization, programming, the ability to communicate with mathematical optimizers, strong interest and experience for work on real-world experiments, and enthusiasm for the project. Proficiency in English is a requirement.
Apply now if you are interested in this PhD position. Send your electronic
application to Professor Jan Swevers: email@example.com
Subject of your email should be: “Embedded optimization for motion Control”.
Include a CV, certificates with university marks, Toefl test results (if applicable),
a list of publications, names and email addresses of two possible references, and a brief description of your research interests are most welcome.
Please quote 10 Academic Resources Daily in your application to this opportunity!