7 papers
Evolutionary Analysis of Continuous-time Finite-state Mean Field Games with Discounted Payoffs
Leonardo Pedroso, Andrea Agazzi, W. P. M. H. Heemels +1
We consider a class of continuous-time dynamic games involving a large number of players. Each player selects actions from a finite set and evolves through a finite set of states.…
Emulation-based Neuromorphic Control for the Stabilization of LTI Systems
Elena Petri, Koen J. A. Scheres, Erik Steur +2
Neuromorphic engineering aims at designing computing and control systems inspired by the neurons and the brain. For the control community, neuromorphic control is an emerging topic…
Nuclear fusion plasma fuelling with ice pellets using a neuromorphic controller
L. L. T. C. Jansen, E. Petri, M. van Berkel +1
In reactor-grade tokamaks, pellet injection is the best candidate for core plasma fuelling. However, density control schemes that can handle the hybrid nature of this type of fuell…
Counterexample-Guided Synthesis of Robust Discrete-Time Control Barrier Functions
Erfan Shakhesi, Alexander Katriniok, W. P. M. H. Heemels
Learning-based methods have gained popularity for training candidate Control Barrier Functions (CBFs) to satisfy the CBF conditions on a finite set of sampled states. However, sinc…
Rhythmic neuromorphic control of a pendulum: A hybrid systems analysis
E. Petri, R. Postoyan, W. P. M. H. Heemels
Neuromorphic engineering is an emerging research domain that aims to realize important implementation advantages that brain-inspired technologies can offer over classical digital t…
Distributed Design of Ultra Large-Scale Control Systems: Progress, Challenges, and Prospects
Leonardo Pedroso, Pedro Batista, W. P. M. H. Heemels
The transition from large centralized complex control systems to distributed configurations that rely on a network of a very large number of interconnected simpler subsystems is on…
Cooperative nonlinear distributed model predictive control with dissimilar control horizons
Paula Chanfreut, José M. Maestre, Quanyan Zhu +1
In this paper, we introduce a nonlinear distributed model predictive control (DMPC) algorithm, which allows for dissimilar and time-varying control horizons among agents, thereby a…