Back to Search
Start Over
Neural-network-based average tracking for nonlinear multi-agent systems with switching topologies
- Source :
- 2020 Chinese Control And Decision Conference (CCDC).
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- This paper investigates the average tracking problem for a class of nonlinear multi-agent systems with switching topologies. The control design is developed for switching topologies without requiring the accurate mode with nonlinear dynamics. An adaptive neural-network-based control algorithm is proposed for a team of agents to track the average of multiple time-varying reference signals, of which the dynamics of each subsystem is assumed to be unknown and will be estimated by using adaptive neural network mechanism. Finally, a numerical simulation is given to illustrate the effectiveness of presented consensus protocol.
- Subjects :
- 0209 industrial biotechnology
Computer simulation
Artificial neural network
Computer science
Multi-agent system
020208 electrical & electronic engineering
Topology (electrical circuits)
02 engineering and technology
Tracking (particle physics)
Network topology
Nonlinear system
020901 industrial engineering & automation
Control theory
0202 electrical engineering, electronic engineering, information engineering
Protocol (object-oriented programming)
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 Chinese Control And Decision Conference (CCDC)
- Accession number :
- edsair.doi...........edf9ff7a14ca63d771ae4f9ed582c582