Unmanned aerial vehicle (UAV) networks are playing an important role in various areas due
to their agility and versatility, which have attracted significant attentions from both the …

This paper presents a combined Nonlinear Model Predictive Control (NMPC) for position
and velocity tracking of underactuated surface vessels, and collision avoidance of static and …

We employ the proximal averaged Newton-type method for optimal control (PANOC) to
solve obstacle avoidance problems in real time. We introduce a novel modeling framework …

With the rapid development of autonomous driving, collision avoidance has attracted
attention from both academia and industry. Many collision avoidance strategies have …

This paper proposes a double-layer model predictive control (MPC) algorithm for the
integrated path planning and trajectory tracking of autonomous vehicles on roads. The …

Nonconvex, nonlinear optimal control problems for large-scale networked control systems
(NCSs) can be distributed to accelerate computation time. One distribution strategy is priority …

Die vorliegende Dissertation ist während meiner Forschungsarbeit am Institut für
Regelungstechnik (IRT) der RWTH Aachen University im Rahmen des Graduiertenkollegs …

Centralized decision-making for a Networked Control System (NCS) suffers from a high
computational burden on the planning agent. Distributed agents, which compute …

This paper presents a dynamic collision avoidance controller of a connected vehicle group
using Model Predictive Control (MPC). The vehicles should follow a predefined reference …

This study presents a self‐triggered distributed model predictive control algorithm for the
flock of a multi‐agent system. All the agents in a flock are endowed with the capability of …