Abstract
This paper considers a cooperative tracking problem for a group of nonlinear multiagent systems under a directed graph that characterizes the interaction between the leader and the followers. All the networked systems can have different dynamics and all the dynamics are unknown. A neural network (NN) with flexible structure is used to approximate the unknown dynamics at each node. Considering that the leader is a neighbor of only a subset of the followers and the followers have only local interactions, we introduce a cooperative dynamic observer at each node to overcome the deficiency of the traditional tracking control strategies. An observer-based cooperative controller design framework is proposed with the aid of graph tools, Lyapunov-based design method, self-structuring NN, and separation principle. It is proved that each agent can follow the active leader only if the communication graph contains a spanning tree. Simulation results on networked robots are provided to show the effectiveness of the proposed control algorithms. © 2012 IEEE.
| Original language | English |
|---|---|
| Article number | 6689304 |
| Pages (from-to) | 1496-1507 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Neural Networks and Learning Systems |
| Volume | 25 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - Aug 2014 |
| Externally published | Yes |
Funding
This work was supported in part by the National Natural Science Foundation of China under Grant 61273108 and Grant 61134001, in part by the Natural Science Foundation Project of CQ CSTC under Grant 2011BB2056, in part by the Major State Basic Research Development Program 973 under Grant 2012CB215202, in part by the Fundamental Research Funds for the Central Universities 106112013CDJZR175501, and in part by SRF for ROCS, SEM.
Keywords
- Adaptive control
- consensus
- cooperative control
- neural network (NN)
- tracking control