Optimization of the closed-loop controller of a discontinuous capsule drive using a neural network
Abstract
In this paper, construction of a neural-network based, closed-loop control of a discontinuous capsule drive is analyzed. The foundation of the designed controller is an optimized open-loop control function. A neural network is used to determine the dependence between the open-loop controller's output and the system's state. Robustness of the neural controller with respect to variation of parameters of the controlled system is analyzed and compared with the original, optimized open-loop control. It is expected that the presented method can facilitate construction of closed-loop controllers of systems, for which other methods are not effective, such as non-smooth or discontinuous ones.
Keywords
Cite
@article{arxiv.2209.00053,
title = {Optimization of the closed-loop controller of a discontinuous capsule drive using a neural network},
author = {Sandra Zarychta and Marek Balcerzak and Volodymyr Denysenko and Andrzej Stefanski and Artur Dabrowski and Stefano Lenci},
journal= {arXiv preprint arXiv:2209.00053},
year = {2023}
}
Comments
23 pages, 7 figures, submitted to Meccanica, Special Issue on Self-Propelled Robots: from Theory to Applications