A Neural Predictive Controller For Underwater Robotic Applications

Workshop on Neural Network Applications and Tools Pub Date : 1993-09-13 DOI:10.1109/NNAT.1993.586063

V. Kodogiannis, P.J.G. Lisboa, J. Lucas

引用次数: 4

Abstract

Oceanographic exploration is one of the fast emerging applications of robotics. The design of Underwater Robotic Vehicles (URV’s), is as challenging as for land based ones. The dificulties in modelling an URV and its hazardous environment restrict the use of conventional controllers. In this paper the application of Neural networks (NNs) for the modelling and control of a prototype URV, which is an example of a system containing non-linearities, is described. A NN model is developed and then incorporated into a predictive control strategy which it is evaluated both in simulation and on-line. Results are shown for both the modelling and control of the system, including hybrid control strategies which combine neural predictive with conventional three term controllers.

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用于水下机器人的神经预测控制器

海洋勘探是机器人技术快速发展的应用领域之一。水下机器人车辆(URV’s)的设计与陆地机器人一样具有挑战性。URV及其危险环境建模的困难限制了传统控制器的使用。本文以一个非线性系统为例，介绍了神经网络在原型URV建模和控制中的应用。建立了一个神经网络模型，并将其纳入预测控制策略，并进行了仿真和在线评估。结果显示了系统的建模和控制，包括将神经预测与传统的三项控制器相结合的混合控制策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Workshop on Neural Network Applications and Tools

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