Article
Version 1
Preserved in Portico This version is not peer-reviewed
Artificial Intelligence Enhanced UUV Actuator Control
and
*
Version 1
: Received: 23 December 2022 / Approved: 5 January 2023 / Online: 5 January 2023 (10:23:48 CET)
A peer-reviewed article of this Preprint also exists.
Wang, Z.; Sands, T. Artificial Intelligence-Enhanced UUV Actuator Control. AI 2023, 4, 270-288. Wang, Z.; Sands, T. Artificial Intelligence-Enhanced UUV Actuator Control. AI 2023, 4, 270-288.
Abstract
This manuscript compares deterministic artificial intelligence to model following control applied to DC motor control, including evaluation of the threshold computation rate to let unmanned underwater vehicles correctly follow the challenging discontinuous square wave command signal. The approaches presented in the main text are validated in MATLAB®, where the motor process is discretized at multiple step sizes, which is inversely proportional to the computation rate. The performance is evaluated by the error mean and standard deviation. With a large step size, discrete deterministic artificial intelligence shows a larger error mean than the model-following self-turning regulator approach (benchmark selection). However, the performance gets optimized with the step size decreased. The error mean is close to the continuous deterministic artificial intelligence when the step size is reduced to 0.2 seconds, which means that the computation rate and the sampling period restrict discrete deterministic artificial intelligence. In that case, the continuous deterministic artificial intelligence is the most feasible and reliable selection for future applications on unmanned underwater vehicles since it is superior to all the approaches with multiple computation rates.
Keywords
artificial general intelligence; intelligent robotics; oceanic robots; unmanned underwater vehicle (UUV); deterministic artificial intelligence; model-following; recursive least squares; marine actuators; self-tuning regulators
Subject
Engineering, Marine Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
