Nonlinear Reduced-Order Observer-Based Predictive Control for Diving of an Autonomous Underwater Vehicle
Xuliang Yao,
Guangyi Yang and
Yu Peng
Discrete Dynamics in Nature and Society, 2017, vol. 2017, 1-15
Abstract:
The attitude control and depth tracking issue of autonomous underwater vehicle (AUV) are addressed in this paper. By introducing a nonsingular coordinate transformation, a novel nonlinear reduced-order observer (NROO) is presented to achieve an accurate estimation of AUV’s state variables. A discrete-time model predictive control with nonlinear model online linearization (MPC-NMOL) is applied to enhance the attitude control and depth tracking performance of AUV considering the wave disturbance near surface. In AUV longitudinal control simulation, the comparisons have been presented between NROO and full-order observer (FOO) and also between MPC-NMOL and traditional NMPC. Simulation results show the effectiveness of the proposed method.
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/DDNS/2017/4394571.pdf (application/pdf)
http://downloads.hindawi.com/journals/DDNS/2017/4394571.xml (text/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:4394571
DOI: 10.1155/2017/4394571
Access Statistics for this article
More articles in Discrete Dynamics in Nature and Society from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().