Study of Genetic Algorithms on Optimizing PI Parameters in Prime Mover Simulation System
- Lixin Tan
- Juemin Liu
Abstract
This paper proposes using the genetic algorithms to optimize the PI regulator parameter in the prime mover simulation system. In this paper, we compared the step response characteristics under the conditions of the genetic algorithms and traditional method by MATLAB simulation and field test tested the dynamic characteristics of the prime mover simulation system. The results proved that genetic algorithms can optimize PI parameters quickly .With this method the prime mover simulation system can meet the requirements of dynamic performance simulation.- Full Text:
PDF
- DOI:10.5539/cis.v1n4p172
Journal Metrics
WJCI (2020): 0.439
Impact Factor 2020 (by WJCI): 0.247
Google Scholar Citations (March 2022): 6907
Google-based Impact Factor (2021): 0.68
h-index (December 2021): 37
i10-index (December 2021): 172
(Click Here to Learn More)
Index
- Academic Journals Database
- BASE (Bielefeld Academic Search Engine)
- CiteFactor
- CNKI Scholar
- COPAC
- CrossRef
- DBLP (2008-2019)
- EBSCOhost
- EuroPub Database
- Excellence in Research for Australia (ERA)
- Genamics JournalSeek
- Google Scholar
- Harvard Library
- Infotrieve
- LOCKSS
- Mendeley
- PKP Open Archives Harvester
- Publons
- ResearchGate
- Scilit
- SHERPA/RoMEO
- Standard Periodical Directory
- The Index of Information Systems Journals
- The Keepers Registry
- UCR Library
- Universe Digital Library
- WJCI Report
- WorldCat
Contact
- Chris LeeEditorial Assistant
- cis@ccsenet.org