Back to Search
Start Over
Observer-based adaptive neural sliding mode trajectory tracking control for remotely operated vehicles with thruster constraints.
- Source :
-
Transactions of the Institute of Measurement & Control . Sep2021, Vol. 43 Issue 13, p2960-2971. 12p. - Publication Year :
- 2021
-
Abstract
- For a class of remotely operated vehicle (ROV) systems with thruster constraints, immeasurable states, and unknown nonlinearities, the trajectory tracking control problem was discussed in this paper. The unknown nonlinear functions were approximated by radial basis function (RBF) neural networks. An adaptive state observer based on neural networks was designed and the immeasurable states were estimated. Considering the problem of thruster saturation constraints, an auxiliary system for saturation compensation was designed and a saturation factor was constructed by the auxiliary system state. By applying the backstepping design method, an adaptive neural sliding mode trajectory tracking controller was developed, in which the saturation factor is contained in adaptive laws. It was proved that the uniformly ultimately bounded (UUB) of trajectory tracking errors can be obtained. Finally, the effectiveness of the proposed trajectory tracking control approach was checked by simulations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01423312
- Volume :
- 43
- Issue :
- 13
- Database :
- Academic Search Index
- Journal :
- Transactions of the Institute of Measurement & Control
- Publication Type :
- Academic Journal
- Accession number :
- 151910886
- Full Text :
- https://doi.org/10.1177/01423312211004819