Publications
Chosen filters:
Chosen filters:
Adaptive control of compliant robots with Reservoir Computing Ghent University
In modern society, robots are increasingly used to handle dangerous, repetitive and/or heavy tasks with high precision. Because of the nature of the tasks, either being dangerous, high precision or simply repetitive, robots are usually constructed with high torque motors and sturdy materials, that makes them dangerous for humans to handle. In a car-manufacturing company, for example, a large cage is placed around the robotU+2019s workspace that ...
A Study of Partial Synchronization in Networks of Delay-Coupled Systems KU Leuven
This thesis studies partial synchronization in networks of delay-coupled systems. Partial synchronization refers to the phenomenon that coupled systems can be grouped into clusters such that synchrony is only observed within each cluster. The coupling considered here contains a time-delay. A pattern of partial synchronization can be characterized by a partial synchronization manifold which is a linear invariant subspace of the state space of the ...
On the graph and systems analysis of reversible chemical reaction networks with mass action kinetics Ghent University
Analysis of control interactions in multi-infeed VSC HVDC connections KU Leuven
The number of voltage-source converters connected to the power system is increasing. This has led to concerns about the impact of control interactions between converters and their influence on the system stability. Recent grid codes consider such interactions as low-frequency disturbances between the converters and neglect network dynamics. This paper studies the control interactions and interferences in a multi-infeed power system with two ...
Pattern Prediction in Networks of Diffusively Coupled Nonlinear Systems KU Leuven
© 2018 In this paper, we present a method aiming at pattern prediction in networks of diffusively coupled nonlinear systems. Interconnecting several globally asymptotical stable systems into a network via diffusion can result in diffusion-driven instability phenomena, which may lead to pattern formation in coupled systems. Some of the patterns may co-exist which implies the multi-stability of the network. Multi-stability makes the application of ...
Distributed observer and controller design for spatially distributed systems KU Leuven
This paper tackles networked distributed observer and controller design problem over directed graph topology for spatially interconnected systems. Traditional centralized design methods suffer from a lack of adaptability to graph variations incurred by network reconfiguration, communication failures, and redundant sensors integration. In this paper, to handle the foregoing limitations imposed by centralized design, state observers are designed ...
Intelligent control of a tractor-implement system using type-2 fuzzy neural networks KU Leuven
Automatic guidance of agricultural vehicles would lighten the job of the operator, while accuracy is needed to obtain an optimal yield. Accurately navigating a tractor consists of controlling different dynamic subsystems (steering and speed). Instead of modeling the subsystem interaction prior to model-based control, we have developed a control algorithm which learns the interactions on-line from the measured feedback error. In this approach, a ...
Testing a community network testbed control system University of Antwerp
Development and continuous operation of network management systems is a major challenge to future networks, where a large number of semi-independent devices jointly try to realize a working network. This work considers network testbed management, and more specifically on testbed management software for community networks. Because of the inherently unstructured and chaotic nature of community networks, managing components inside a community ...
Adaptive Neuro-Fuzzy Control of a Spherical Rolling Robot Using Sliding-Mode-Control-Theory-Based Online Learning Algorithm KU Leuven
As a model is only an abstraction of the real system, unmodeled dynamics, parameter variations, and disturbances can result in poor performance of a conventional controller based on this model. In such cases, a conventional controller cannot remain well tuned. This paper presents the control of a spherical rolling robot by using an adaptive neuro-fuzzy controller in combination with a sliding-mode control (SMC)-theory-based learning algorithm. ...