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Proceedings Paper

CMAC neural network architecture for control of an autonomous undersea vehicle
Author(s): Rick F. Comoglio; Abhijit S. Pandya
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Paper Abstract

The design of an autonomous undersea vehicle (AUV) control system is a significant challenge in light of the highly uncertain nature of the ocean environment together with partially known nonlinear vehicle dynamics. This paper describes a neural network architecture called Cerebellar Model Arithmetic Computer (CMAC). CMAC is used to control a model of an autonomous underwater vehicle. The AUV model consists of two input parameters, the rudder and stern plane deflections, controlling six output parameters; forward velocity, vertical velocity, pitch angle, side velocity, roll angle, and yaw angle. Properties of CMAC and results of computer simulations for identification and control of the AUV model are presented.

Paper Details

Date Published: 16 September 1992
PDF: 11 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.140030
Show Author Affiliations
Rick F. Comoglio, Florida Atlantic Univ. (United States)
Abhijit S. Pandya, Florida Atlantic Univ. (United States)

Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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