[en] In the realm of control systems and robotics, the quest for intelligent and adaptive controllers has led researchers to draw inspiration from the intricate workings of the human brain. This pursuit has prompted a departure from traditional control concepts. Traditional control, often expressed in terms of continuous-time signals, contrasts with the largely event-based nature of neurons.
To be able to use these concepts and models in a control workflow, we present a toolbox that provides blocks based on the work of Ribar et al. to quickly create neuronal circuits that can be inserted in a control loop. This allows modeling, design, and testing of neuromorphic controllers to be far quicker and accessible to a wider audience.
Research Center/Unit :
Montefiore Institute - Montefiore Institute of Electrical Engineering and Computer Science - ULiège
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Fernandez Lorden, Christian ; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science
Forni Fulvio; University of Cambridge > Department of Engineering > Control
Drion, Guillaume ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Systèmes et modélisation
Sacré, Pierre ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Robotique intelligente
Franci, Alessio ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Brain-Inspired Computing
