Intelligent control for a remotely operated vehicle

Abstract

This article considers the tracking control problem of an underwater vehicle used in the exploitation of combustible gas deposits at great sea depths. The vehicle is subjected to different load configurations that introduce considerable variations of its mass and inertial parameters. In this work it is assumed that the possible vehicle configurations are known, but the time instants when the changes occur and the new vehicle configuration following the change are unknown. A neural network-based switching control is proposed for the considered mode-switch process. This solution simplifies the control scheme implementation and reduces the control signal chattering.

Keywords:

• switching supervisory control
• neural networks
• mode switch process
• remotely operated vehicle

Acknowledgement

Thanks to the anonymous reviewers for their constructive and helpful comments to the original manuscript.