Abstract
In this paper, we address the problem of steering Lagrange system to track targets with unknown trajectory in the presence of modeling uncertainties and actuation faults. Artificial neural network technique is employed to reconstruct the behavior of the targets with unknown trajectory, with which robust adaptive fault-tolerant tracking control algorithms are developed. The developed control scheme is able to cope with unknown desired trajectory, attenuate modeling uncertainties and accommodate actuation faults. The proposed control scheme is shown to be able to maintain close target tracking despite actuation ineffectiveness and desired trajectory uncertainty. The benefits and feasibility of the developed control are also confirmed by simulations.
| Original language | English |
|---|---|
| Pages (from-to) | 3913-3920 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Industrial Electronics |
| Volume | 64 |
| Issue number | 5 |
| Early online date | 23 Dec 2016 |
| DOIs | |
| Publication status | Published - May 2017 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 1982-2012 IEEE.
Funding
This work was supported in part by the Major State Basic Research Development Program 973 (No. 2014CB249200), in part by the technology transformation program of Chongqing higher education university (KJZH17102), and in part by the National Natural Science Foundation of China (No. 61134001).
Keywords
- Actuation faults
- Lagrange system
- Neural network (NN)
- Unknown target