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Autonomous underwater vehicles

Autonomous underwater vehicles

Abstract

usc Refereed/Peer-reviewed The chapter deals with the development of indirect adaptive controllers based on Fuzzy Control approach for Autonomous Underwater Vehicles (AUVs). The non-linear, coupled and time-varying dynamics of AUVs necessitates the development of adaptive controllers. The on-line identification and adaptation of the controller is carried out using the fuzzy approach. The methodology uses the input-output data to come up with a structure for the controller and optimal adaptation of the parameters to achieve the required accuracy. The Semi-Serial-Parallel- Model is employed both for identification and control. Initial validation of the identification results are carried out numerically using a mathematical model. Hardware-in-loop (HIL) simulations are presented to validate the controller before carrying out the experiments. Experimental results show that the proposed controller is capable of suitably controlling the AUV in real environment and demonstrate its robust characteristics.

Country
Australia
Related Organizations
Keywords

model-based adaptive control, auto generating mechanism, AUV, fuzzy network, system identification

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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