With this research program, we want to optimise the performances of cyber-physical systems in a powerful way. By making these systems adaptable to changing operating conditions and connecting them to identical or similar systems, the level of performance will increase considerably.
CONTROL WITH SITUATION INFORMATION
Many industrial project partners have applications which performances would improve significantly if autonomous motion control systems could respond to changing situations. However, due to a limited computing capacity, the complexity of this motion control system must be restricted to qualify for model-based predictive control. This project ran from June 2014 up to and including August 2016 and developed generic technologies allowing to create autonomous motion control systems. The knowledge partners can use them in various industrial areas.
Click here to watch the SITcontrol project video
ENVIRONMENTAL MODELLING FOR AUTOMATED DRIVING AND ACTIVE SAFETY
This project fits within Flanders Make’s broader research efforts into vehicle automation, with particular focus on public transport. It includes, among others, a self-driving bus that is able to analyse its own environment and, as such, can travel in a safe, comfortable and energy-efficient way. As an open research platform, this bus can enable Flemish companies to develop new technologies, services and products. This will assure them of a solid starting position in the supply chain of a market, which – according to the estimates – will rapidly grow within the next 10 years. This project runs from April 2015 up to June 2017.
ROBUST AND FAST LEARNING CONTROL
Industrial systems often work according to complex and dynamic processes and must execute time and again similar (but not perfectly repetitive) tasks. Robustly designed controllers and advanced adjustment and calibration procedures are a must to properly control these systems. In this context, learning controllers are preferable to techniques based on connection and feedback mechanisms. They can register performances from earlier task executions to learn from them and adjust and optimise subsequent executions. This project runs from March 2016 to February 2018 and studies such learning control algorithms to show and validate their practical potential for industrial systems.
ROBUST AND OPTIMAL CONTROL OF SYSTEMS OF INTERACTING SUBSYSTEMS
Engineers often struggle with the robust control of complex processes such as mechatronic systems, components of production machines and vehicle systems. With this project, Flanders Make wants to address the strong demand from the Flemish industry for reliable and efficient control design software that can adequately cope with the complex behaviour of systems of interacting subsystems. We also need software that supports the selection of a complex controller configuration (according to a/o number, type and position of sensors and actuators), preferably with a user-friendly interface that automates the design process. Researchers are studying these issues from March 2016 to February 2020. It should lead to better performances, lower costs and an earlier return on investments.