Journal article
Adaptive Reference Management and Model Predictive Control for Near-Surface Operations of Autonomous Underwater Vehicles
IFAC-PapersOnLine, Vol.59(22), pp.423-428
2025
DOI: 10.1016/j.ifacol.2025.11.670
Abstract
Low-speed near-surface operations for autonomous underwater vehicles (AUVs) provide unique control challenges as a result of significant forces from suction and waves as well as reduced control authority from control surfaces. These facts motivate the development of an optimal, adaptive control scheme capable of managing these challenges. In particular, this work focuses on the problem of tracking desired depth profiles of a generic submarine. A model predictive controller (MPC) is presented based on a linearized reduced-order model (ROM) and an L1 adaptive control algorithm, which is used to modify the MPC reference commands to overcome nonlinearities and uncertainties within the model. The efficacy of this methodology is demonstrated with results from the Joubert BB2 ROM.
Details
- Title: Subtitle
- Adaptive Reference Management and Model Predictive Control for Near-Surface Operations of Autonomous Underwater Vehicles
- Creators
- Maxwell Hammond - Mechanical Engineering Department, University of Iowa, Iowa City, IA 52240 USAGage MacLin - University of IowaVenanzio Cichella - Mechanical Engineering Department, University of Iowa, Iowa City, IA 52240 USA
- Resource Type
- Journal article
- Publication Details
- IFAC-PapersOnLine, Vol.59(22), pp.423-428
- DOI
- 10.1016/j.ifacol.2025.11.670
- ISSN
- 2405-8963
- eISSN
- 2405-8963
- Publisher
- Elsevier Ltd
- Number of pages
- 6
- Language
- English
- Date published
- 2025
- Academic Unit
- Mechanical Engineering
- Record Identifier
- 9985091810302771
Metrics
1 Record Views