Safe and collision-tolerant hybrid high-speed collaborative robots

Accelerating Nonlinear Model Predictive Control through Optimal Control Problem Reformulations

Adaptive robotic grasping and manipulation based on tactile feedback

Bringing Reinforcement Learning to Real-World Mechatronic Systems: A Hybrid Learning Control Approach

Data-Driven Adaptive Operational Strategies for Wind Energy Conversion Systems Incorporating Frequency Containment Reserve

Design and Control of a Robotic Hopping Leg with Soft Artificial Muscles

Design of a high-speed compliant hybrid collaborative robot

Design of a High Torque Density Electric Actuator for Quasi-Direct-Drive Robot Applications

Doctoral project Ahmed Hassan

Doctoral project Arne De Keyser

Doctoral project Jeroen Taets

Doctoral project Lennert De Knop

Doctoral project Milad Sajadi Mian Ab

Doctoral project Olivier Algoet

Doctoral project Omid Heydarnia

Doctoral project Pieter Nguyen Phuc

Doctoral project Tom Lefebvre

Dynamic Bayesian networks for predicting and mitigating failures in mechatronic applications

Dynamic design of motion systems subject to variations using robust adaptive feedforward controllers

Energy flexibility aggregation and coordination with learning-based control

From homogeneous to targeted spray application by system level machine control and field optimization

Generative and Multi-Objective Design of Task-Specific Robotic Manipulators

High Dynamic Collision Tolerant Robot Design

Hybrid Markov Decision Processes for filtering and predicting quality variations in production processes

Hybrid Physics-Based Neural Network Models for Predicting Nonlinear Dynamics in Mechatronic Applications

Integrated wind turbine and wind farm controllers interacting with digital twins

Mapping Robotic Contact Interactions Using Model-Based Tactile Sensing

Merging classical controllers with reinforcement learning for safety critical systems

Model-based control design and commissioning of industrial machines through Bayesian optimization

Model-Based Optimization and Control for Magnetic Particle Targeting in Biomedical Applications

Modelling and optimal path planning for the coating process of oil free compressor screws using robotic painting

Physics-informed neural networks for distributed thermal field reconstruction in electromechanical systems

Probabilistic hybrid modelling for the control design of industrial machines

Remote Electromechanical Actuation Using Electrically Resonant Power Transfer Systems: Design and Optimal Control

Tactile End Effectors for Legged Robotic Locomotion: From Design to Control

Trajectory optimization and control of robotic manipulators

Aero-servo-elastic simulation of airborne wind energy systems

AWEsim: A Geometry-Resolved Aero-Servo-Elastic Framework for Airborne Wind Energy Simulations

Design of a High Torque Density Electric Actuator for Quasi-Direct-Drive Robot Applications

Development of Efficient Simulation Methods for the Coupling between Air Flow, Particle or Yarn Motion, Control and Video Processing

Doctoral project Annelies Coene

Doctoral project Frederik Soetaert

Doctoral project Glenn Van Steenkiste

Doctoral project Muhammad Azeem

Doctoral project Nele De Geeter

Doctoral project Praneet Amitabh

Doctoral project Rembert Daems

Doctoral project Yentl Thielemans

Energy based control design for natural dynamics of robotic systems

Fatigue-aware control strategies for wind turbines

Fiber optics and predictable physical models towards better thermal characterization of electric motors

A new paradigm in discovering nonlinear governing equations from the time evolution of tribological phenomena

Causal Actionable Understanding via a diagnostic Assistant for Interactive Root Cause Analysis (CausAICA_SBO)

Computational-experimental study of advanced hybrid modelling and control techniques for the evaluation of the power flow in vehicle electrification

Control architecture design for physical dynamic systems

CTRL schemes merged with eXplainable AI for t(h)rustworthy control of physical dynamic systems (CTRLxAI=T(H)RUST)

Design and Control of a Robotic Hopping Leg with Soft Artificial Muscles

Design of low frequency metamaterial technology for the electrical power transfer to forces and torques

Detection and avoidance of low probability phenomena using probabilistic graphical models in electromechanical actuators.

Detection and avoidance of low probability phenomena using probabilistic graphical models in electromechanical actuators

Development of surrogate-assisted algorithms for combined design and trajectory optimization of dynamic mechatronic systems

DIRAC - Deterministic and Inexpensive Realizations of Advanced Control

dotation 2018 EEDT-DC

Dotation 2019 - EEDT - DC

Drivetrain Co-design - Physical and control co-design of electromechanical drivetrains for machines and vehicles

DTF-PINN - Reconstructing the Distributed Thermal Field using Physics Informed Neural Networks

Dynamic hybrid models for virtual scenario testing and optimal design of drivetrains

Emodo - Efficient model based design parameter exploration and optimalization in mechatronics

Energy Flexibility Aggregation and Coordination with Learning-based Predictive Control

EVIT - Model-based experimental-virtual testing

FiberMech - Fiber optics & predictable physical models towards load analysis in mechatronic systems

Framework for Systematic Design of Digital Twins - DTDesign

FROGS - Flexible and Robust Robotic Gripping Solutions able to deal with product variability

Hybrid AI for Estimation in Mechatronics

Impact-aware Robot Planning And Control (IRPAC)

InduFlexControl-2 - Control algorithms for flexibility in power-to-X and industrial processes

InduFlexControl - Control algorithms for flexibility in power-to-X and industrial processes

Integrated Identification for Control - ID2CON

Maximum energy yield tracking for renewable energy systems to accommodate the variability of energy sources

MODA - Model-Based Data Analytics

MoForM - Model based force measurements

Motion visualization and analysis through digital twins based on CAD, AI and Vision - CADAIVISION_SBO

MULTISCALE - Transformer based framework for integrating and interpreting multiscale, multirate and multimodal data in mechatronic systems

MULTISENSOR: Multi-sensor system design and validation

Multi-System Learning Control - MultiSysLeCo

Optimization of Electrically Resonant Power Transfer Structures for Remote Rotational and Translational Actuation.

PICASSO - Predicting Coupled Dynamic Systems under Variations

Product-Assembly CoDesign

QUASIMO - Quality via a System Intelligence Methodology

REXPEK - Reproducing Expert Knowledge

Smart, Aware, Integrated Wind Farm Control Interacting with Digital Twins

SMART Grip - Steel Sheet e-Magnetic Automated Retrieval Gripper

Torso bot - a highly performant drivetrain solution for the torso of a humanoid robot

TuPIC - Tuning of Parametrized Industrial Controllers with AI

Developing the tools and insight to expand the Belgian offshore wind farms with airborne wind energy systems

Development of a multi-fidelity approach for aero-servo-elastic modelling of airborne wind energy systems.

DGTwinPrediction - A Digital Twin for Health Monitoring and Predictive Maintenance

Equine arrhythmias: innovations that improve diagnosis, horse welfare and rider’s safety

Physics-enhanced machine learning for domain-aware predictive maintenance.