DocumentCode :
2156873
Title :
System identification of underwater vehicles
Author :
Pereira, Javier ; Duncan, Alec
Author_Institution :
Maritime Eng. CRC, Curtin Univ. of Technol., Bentley, WA, Australia
fYear :
2000
fDate :
2000
Firstpage :
419
Lastpage :
424
Abstract :
The aim of this project was to obtain hydrodynamic derivative measurements from sea trials using an underwater vehicle which is a half-scale model of the PAP-104 mine countermeasures UUV. Trials data were collected for a series of manoeuvres which were then reconstructed to give the required vehicle state estimates. This reconstruction was carried out using an extended Kalman filter. Hydrodynamic derivative estimates were then generated by a stepwise regression algorithm, which took the reconstructed vehicle state and measured vehicle forces as input. Traditionally, these types of hydrodynamic measurements are made using a planar motion mechanism (PMM). Ideally system identification (SI) techniques would provide a more practical alternative, as the UUV need only be driven in a predefined way and the SI techniques applied in order to obtain current hydrodynamic measurements. SI techniques also give measurements based on the overall response of the vehicle and umbilical, which is not the case with PMM measurements
Keywords :
Kalman filters; hydrodynamics; military systems; mobile robots; parameter estimation; state estimation; underwater vehicles; PAP-104 mine countermeasures; extended Kalman filter; half-scale model; hydrodynamics; identification; parameter estimation; state estimation; unmanned underwater vehicles; Acceleration; Australia; Equations; Force measurement; Hydrodynamics; Remotely operated vehicles; Sea measurements; State estimation; System identification; Underwater vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Underwater Technology, 2000. UT 00. Proceedings of the 2000 International Symposium on
Conference_Location :
Tokyo
Print_ISBN :
0-7803-6378-7
Type :
conf
DOI :
10.1109/UT.2000.852581
Filename :
852581
Link To Document :
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