Comparison of novel approaches to the predictive control of a DC-DC boost converter, based on heuristics

Baždarić, Robert (author), Vončina, Danijel (author), Škrjanc, Igor (author)

This paper introduces novel approaches to the predictive control of a DC-DC boost converter and a comparison of the controllers built that consider all of the current objectives and minimize the complexity of the online processing. The primary concern is given to the applicability of the inclined methods for systems that are physically small but considered physically fast processes. Although the performed methodologies are simulated and applied to a DC-DC boost converter, they can have broader applicability for different switched affine systems as a subgroup of the hybrid systems. The introduced methods present an alternative way of building the process model based on the fuzzy identification that contributes to the final objective: the applicability of the predictive methods for fast processes.

• Language: English
• Keywords: fuzzy algorithms, identification, control, switched affine systems, hybrid systems, fuzzy identification, fuzzy modeling, two degrees of freedom, fuzzy model predictive control
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FE - Faculty of Electrical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2018
• Number of pages: 16 str.
• Numbering: Vol. 11, iss. 12, art. 3300
• PID: 20.500.12556/RUL-132066
• UDC: 681.5
• ISSN on article: 1996-1073
• DOI: 10.3390/en11123300
• COBISS.SI-ID: 12264020
• Publication date in RUL: 11.10.2021

Record is a part of a journal

• Title: Energies
• Shortened title: Energies
• Publisher: Molecular Diversity Preservation International
• ISSN: 1996-1073
• COBISS.SI-ID: 518046745

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
• Licensing start date: 01.12.2018

Secondary language

• Language: Slovenian
• Keywords: mehki algoritmi, identifikacija, vodenje