Fuzzy and MRAC based direct torque control for FSTPI fed induction motor

Sudeshna Ghosh (), Harsh Goud (), Chirag Salwan () and Pankaj Swarnkar ()
Additional contact information
Sudeshna Ghosh: Maulana Azad National Institute of Technology
Harsh Goud: Indian Institute of Information Technology
Chirag Salwan: Indian Institute of Information Technology
Pankaj Swarnkar: Maulana Azad National Institute of Technology

International Journal of System Assurance Engineering and Management, 2024, vol. 15, issue 7, No 28, 3225-3233

Abstract: Abstract Direct Torque Control (DTC) for Induction Motor Drives (IMD) has evolved as an industry standard due to numerous advantages like insensitive to variation, simplicity in implementation and quicker dynamic response compared to other vector control techniques. Six Switch Voltage Source Inverter (SSTPI), flux and torque hysteresis controllers characterize the conventional DTC. In this paper an attempt is made to replace the conventional SSTPI with a four switch voltage source inverter (FSTPI) for attaining same performance. Voltage vectors of FSTPI are balanced by proper vector selection using Space Vector Modulation thus imitating SSTPI operation. Selection of most optimum voltage vector ensures superior dynamic response during transient operation. This paper also presents superior speed control using a Fuzzy Logic Controller and Model Reference Adaptive Controller for Direct Torque Control (DTC) of Induction Motor Drive fed with FSTPI. The dynamic performance of FSTP inverter-fed IMD is investigated for different load conditions using proposed schemes along with traditional DTC scheme. Comparison shows that proposed DTC schemes with intelligent and adaptive control algorithm show excellent performance in terms of low torque ripples and speed regulation compared to conventional DTC technique.

Keywords: Model reference adaptive control (MRAC); Fuzzy logic; Induction motor drive (IMD); Four switch three phase inverter (FSTP); Space vector modulation (SVM) (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13198-024-02328-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:15:y:2024:i:7:d:10.1007_s13198-024-02328-5

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-024-02328-5

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().