Loading…

Analysis of methods to optimize control systems for power supply of marine vessels using fuzzy logic and fractal analysis

The paper considers the features of promising methods to optimize the control systems for power supply of marine vessels using fuzzy logic and fractal analysis. In order to design an effective control contour for the power supply system (PSS), it is proposed to use synergistic mechantronic systems b...

Full description

Saved in:
Bibliographic Details
Published in:Journal of physics. Conference series 2021-10, Vol.2061 (1), p.12088
Main Authors: Khekert, E V, Epikhin, A I
Format: Article
Language:English
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The paper considers the features of promising methods to optimize the control systems for power supply of marine vessels using fuzzy logic and fractal analysis. In order to design an effective control contour for the power supply system (PSS), it is proposed to use synergistic mechantronic systems based on intelligent technologies with fundamentally new properties that allow for a more effective solution of control problems using fractal analysis of time series to increase the adequacy of forecasting through in-depth analysis of the causes of emergency situations. The synergistic effect SE of the control within such systems is a set of effects obtained as a result of their combination and synchronization in time and space. Practical aspects of fractal analysis are considered on the example of a two-cycle engine with supercharging and air cooling. In the study of fractal processes, a method is proposed for identifying and eliminating the short-term dependence of the value of the time series of the process S(t) , which is characteristic of autoregressive processes, using regression with respect to S(t-1) and conducting the R/S analysis of the remainder X(t) . Short-term dependence is eliminated provided that long-term dependence is maintained. Autoregressive AR(1) differences are analyzed at a certain time interval for various engine operating modes. The results of the R/S analysis of the engine operation and the determination of the Hurst exponent are used to increase the efficiency of forecasting and control of the PSS in the period of the detected chaotic behavior of the time series.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2061/1/012088