Optimization of the closed-loop controller of a discontinuous capsule drive using a neural network

TL;DR

This paper presents a neural network-based closed-loop controller for a discontinuous capsule drive, improving robustness and effectiveness where traditional methods struggle, by learning the relationship between open-loop control and system state.

Contribution

It introduces a novel neural network approach to control discontinuous systems, leveraging an optimized open-loop control as a foundation for improved robustness.

Findings

Neural controller demonstrates robustness to parameter variations.

Compared to open-loop control, the neural network improves system stability.

Method effectively handles non-smooth, discontinuous system dynamics.

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.