Paper
15 November 1999 Online adaptive and neural network control of underwater vehicles
Myung-Hyun Kim, Daniel J. Inman
Author Affiliations +
Proceedings Volume 3838, Mobile Robots XIV; (1999) https://doi.org/10.1117/12.369261
Event: Photonics East '99, 1999, Boston, MA, United States
Abstract
An adaptive neural network controller has been developed for a model of an underwater vehicle. This controller combines radial basis neural network and sliding mode control techniques. No prior off-line training phase is required and this scheme exploits the advantages of both neural network control and sliding mode control. An on-line stable adaptive law is derived using Lyapunov theory. It is observed that the number of neurons and the width of Gaussian function should be chosen carefully. Performance of the controller is demonstrated by computer simulations.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Myung-Hyun Kim and Daniel J. Inman "Online adaptive and neural network control of underwater vehicles", Proc. SPIE 3838, Mobile Robots XIV, (15 November 1999); https://doi.org/10.1117/12.369261
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Cited by 3 scholarly publications.
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KEYWORDS
Neural networks

Vehicle control

Control systems

Neurons

Systems modeling

Laminated object manufacturing

Mathematical modeling

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