Abstract
This brief investigates the finite-time consensus tracking control problem for networked uncertain mechanical systems on digraphs. A new terminal sliding-mode-based cooperative control scheme is developed to guarantee that the tracking errors converge to an arbitrarily small bound around zero in finite time. All the networked systems can have different dynamics and all the dynamics are unknown. A neural network is used at each node to approximate the local unknown dynamics. The control schemes are implemented in a fully distributed manner. The proposed control method eliminates some limitations in the existing terminal sliding-mode-based consensus control methods and extends the existing analysis methods to the case of directed graphs. Simulation results on networked robot manipulators are provided to show the effectiveness of the proposed control algorithms.
| Original language | English |
|---|---|
| Pages (from-to) | 749-756 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Neural Networks and Learning Systems |
| Volume | 29 |
| Issue number | 3 |
| Early online date | 29 Dec 2016 |
| DOIs | |
| Publication status | Published - Mar 2018 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
Funding
This work was supported in part by the National Natural Science Foundation of China under Grant 61673077 and 61273108, in part by the Basic and Advanced Research Project of Chongqing under Grant CSTC2016jcyjA0361.
Keywords
- Consensus
- cooperative control
- networked mechanical systems
- neural networks (NNs)
- terminal sliding mode