SPP 1914 - Cyber-Physical Networking: Kooperative Regelung und Topologiekontrolle für eng in großen drahtlosen Netzen gekoppelte autonome Agenten


Project Title
SPP 1914 - Cyber-Physical Networking: Cooperative and Topology Control for Tightly Coupled Large-Scale Wireless Networked Autonomous Agents
 
Funding Code
WE 2176/14-2
 
 
Principal Investigator
 
Status
Laufend
 
Duration
16-12-2019
-
15-12-2022
 
GEPRIS-ID
 
 
Funding Program
SPP 1914 - Cyber-Physical Networking
 
 
Project Abstract
In this project we consider cooperative control of mobile agents that interact over a wireless network. The network is set up by the nodes, i.e. no external communication infrastructure is assumed. The project goal is to develop analysis and synthesis tools that allow joint design of distributed cooperative control and communication strategies for large homogeneous groups of mobile agents which interact via a wireless network. The overall control performance expressed in terms of a suitably defined l2 performance channel depends on the local dynamic control of individual agents as well as on flow of information between agents. It is restricted by imperfections of the communication network, in particular by packet loss and time delay, as well as possibly quantization effects resulting from low bit rates. The goal is to derive conditions on the stability and the performance of multi-agent systems that depend on the decision variables of the design. These variables are the control gains, the communication network parameters and the network topology. The project will continue with our study of time-triggered distributed control of wireless networked agents. We develop tools for trading network demands against control demands in an architecture which facilitates the decoupling of stochastic aspects of wireless networks and deterministic control of agent dynamics. We study with distributed consensus and flocking two core building blocks for control of multi-agent systems. In addition to concepts well understood for time-triggered control, we will explore the potential of event-triggered control as well as event-triggered model predictive control for more efficient use of channel capacity. Our theoretical results will be substantiated by simulation studies and practical experiments with AUVs and UAVs.