LeCoPro - Learning control for production machines
From 01-09-2009 to 31-08-2013
Description
Up till now, only a few implementations of learning controllers have been realized for mechatronic systems. Moreover, only model-based techniques were adapted and only implementations were done on small, relatively simple mechatronic subsystems. In a first track of the LeCoPro-project, the potential of different learning control algorithms for more complex mechatronic (sub)systems will be investigated. The advantages and drawbacks of model-based learning control methods (Iterative Learning Control – ILC; Model Predictive Control - MPC), suitable for the control of systems of limited complexity, and non-model-based methods (Machine Learning), suitable for the control of more complex systems, will be compared. State-of-the-art techniques in these research domains will be extended and adapted to address the specific features of mechatronic systems (fast non-linear dynamics, uncertainty of system parameters, stringent stability and robustness requirements, etc.).
Many production machines consist of strongly interacting subsystems, each responsible for a different mechatronic subtask. Most of these systems are controlled in a decentralized way, because of flexibility, modularity and scalability reasons. To address such control configurations, in a second track of the project global learning controllers will be developed for machines with interacting subsystems that are controlled in a decentralized manner. Nowadays controller parameters of subsystems in such production machines are tuned independently. This often results in an unsatisfactory behaviour of the global system, since this approach does not take the interaction between the subsystems into account. The objective of the LeCoPro-project in this track is to develop global learning controllers, which learn the optimal coordination of the decentralised control actions for each individual subsystem such that a global optimum is obtained. Similar to the track on subsystem controllers, also in this track model-based as well as non-model-based (global) learning control techniques will be developed.
Since the practical applicability of all developed methodologies is a prerequisite of the LeCoPro-project, a significant part of the planned work is dedicated to practical validation of these methodologies. At least one generic test benches will be designed and built within the scope of the project, on which the practical performance of the different learning control techniques will be evaluated. On this test bench, the effectiveness of different learning controllers with respect to improvement of the system productivity in comparison with the actual situation and efficiency of implementation will be extensively demonstrated. This will not only allow a systematic comparison of different techniques to be carried out, but moreover provide a direct evidence for the Flemish machine-building companies of the industrial potential of the developed learning strategies.
Team
- Moritz Diehl, Co-promoter
Financing
Funding: IWT - Agentschap voor Innovatie door Wetenschap en Technologie
Program/Grant Type: IWT SBO - IWT Projects Strategic Basic Research
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
STADIUS Alumni Herman Verrelst – new CEO of Biocartis
08 June 2017
Herman Verrelst, the founder of KU Leuven spin-off Cartagenia, who has been working in Silicon Valley, US for the last few years will be returning to Belgium to follow the steps of Rudi Pauwels as CEO of the Belgian diagnostic company, Biocartis.
Supporting healthcare policymaking via machine learning – batteries included!
29 May 2017
STADIUS takes the lead in the data analytics efforts in an ambitious European Project MIDAS.
Marc Claesen gives an interview about his PhD for the magazine of the Faculty of Engineering Sciences "Geniaal"
10 February 2017
Did you know that in Belgium approximately one third of type 2 diabetes patients are unaware of their condition?
Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.