Neural adaptive control for flocking of Agents with unknown nonlinear dynamics

DOI

10.2991/icmse-15.2015.8How to use a DOI?

Keywords

distributed control;neural networks; adaptive flocking ;unknown nonlinear dynamics;

Abstract

This paper is concerned with the leader-follower flocking problem of networked nonholonomic multi-agent systems with non-identical unknown nonlinear dynamics. The leader motion to be synchronized is also non-linear and unknown. By employing the graph theory and a pinning control technique,a distributed neural adaptive control design is developed for the agents to achieve motion synchronization with the leader.The design is for a directed communication graph with a fixed topology.A collective potential function is used to maintain cohesion between the agents. On the basis of Lyapunov analysis,the developed neural flocking algorithm guarantees that all the agents’ headings and speeds are synchronized with the leader and collisions between the agents can be avoided.An illustrative example is given to show the effectiveness of the proposed control strategy which may be applied to surveying in the civil engineering.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaowei Qi
AU  - Guang Ren
PY  - 2015/12
DA  - 2015/12
TI  - Neural adaptive control for flocking of Agents with unknown nonlinear dynamics
BT  - Proceedings of the 2015 6th International Conference on Manufacturing Science and Engineering
PB  - Atlantis Press
SP  - 41
EP  - 44
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-15.2015.8
DO  - 10.2991/icmse-15.2015.8
ID  - Qi2015/12
ER  -