Experimentally verified depth regulation for AUVs using constrained model predictive control
Experimentally verified depth regulation for AUVs using constrained model predictive control
In the application of an autonomous underwater vehicle a critical requirement is to keep the level of the actuation signals within operational limits to avoid, for example, actuator nonlinearities and reduce peak power consumption. The most common approach to this problem for AUVs that have been deployed is, if required, to trade-off performance in order to keep the actuation signals and power required within the operational limits. This paper addresses depth control of an AUV using model predictive control with constraints on the both the amplitude and rate of change of the entries in the control vector. The model predictive control algorithm is designed by solving a quadratic programming problem in real-time when implemented on an AUV prototype. Experimental test results for depth control are also given and demonstrate that physically relevant constraints on the thrust and actuation power, critical factors for the use of these vehicles, can be achieved. Moreover, there is agreement between the control action used and the underlying physics of a body moving in water.
constrained control, control of fluid flows and fluids-structures interactions, real-time control
11974-11979
International Federation of Automatic Control
Steenson, Leo
91b88ead-e3ac-49e8-bff6-fdce0b8b7c0e
Wang, Luyping
27413cbd-4d71-4ac6-81df-266a5f6b0890
Phillips, Alexander
f565b1da-6881-4e2a-8729-c082b869028f
Turnock, Stephen
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Furlong, Maaten
332e9aef-8c6b-452f-8b85-712492767458
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72
2014
Steenson, Leo
91b88ead-e3ac-49e8-bff6-fdce0b8b7c0e
Wang, Luyping
27413cbd-4d71-4ac6-81df-266a5f6b0890
Phillips, Alexander
f565b1da-6881-4e2a-8729-c082b869028f
Turnock, Stephen
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Furlong, Maaten
332e9aef-8c6b-452f-8b85-712492767458
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72
Steenson, Leo, Wang, Luyping, Phillips, Alexander, Turnock, Stephen, Furlong, Maaten and Rogers, Eric
(2014)
Experimentally verified depth regulation for AUVs using constrained model predictive control.
Boje, Edward and Xia, Xiaohua
(eds.)
In Proceedings of the 19th IFAC World Congress.
International Federation of Automatic Control.
.
(doi:10.3182/20140824-6-ZA-1003.01497).
Record type:
Conference or Workshop Item
(Paper)
Abstract
In the application of an autonomous underwater vehicle a critical requirement is to keep the level of the actuation signals within operational limits to avoid, for example, actuator nonlinearities and reduce peak power consumption. The most common approach to this problem for AUVs that have been deployed is, if required, to trade-off performance in order to keep the actuation signals and power required within the operational limits. This paper addresses depth control of an AUV using model predictive control with constraints on the both the amplitude and rate of change of the entries in the control vector. The model predictive control algorithm is designed by solving a quadratic programming problem in real-time when implemented on an AUV prototype. Experimental test results for depth control are also given and demonstrate that physically relevant constraints on the thrust and actuation power, critical factors for the use of these vehicles, can be achieved. Moreover, there is agreement between the control action used and the underlying physics of a body moving in water.
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More information
Published date: 2014
Venue - Dates:
19th IFAC World Congress, Cape Town, South Africa, 2014-08-24 - 2014-08-29
Keywords:
constrained control, control of fluid flows and fluids-structures interactions, real-time control
Organisations:
Electronics & Computer Science, Civil Maritime & Env. Eng & Sci Unit, Ocean Technology and Engineering
Identifiers
Local EPrints ID: 370258
URI: http://eprints.soton.ac.uk/id/eprint/370258
PURE UUID: 626a4078-3c9b-4e97-9b11-2a523151c0ed
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Date deposited: 20 Oct 2014 13:49
Last modified: 15 Mar 2024 03:21
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Contributors
Author:
Leo Steenson
Author:
Luyping Wang
Author:
Alexander Phillips
Author:
Maaten Furlong
Author:
Eric Rogers
Editor:
Edward Boje
Editor:
Xiaohua Xia
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