CMAC neural network architecture for control of an autonomous undersea vehicle

Rick F. Comoglio; Abhijit S. Pandya

doi:10.1117/12.140030

16 September 1992 CMAC neural network architecture for control of an autonomous undersea vehicle

Rick F. Comoglio, Abhijit S. Pandya

Proceedings Volume 1709, Applications of Artificial Neural Networks III; (1992) https://doi.org/10.1117/12.140030
Event: Aerospace Sensing, 1992, Orlando, FL, United States

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.

Citation Download Citation

Rick F. Comoglio and Abhijit S. Pandya "CMAC neural network architecture for control of an autonomous undersea vehicle", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.140030

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