Optimum of fractional order fuzzy logic controller with several evolutionary optimization algorithms for inverted pendulum
Optimum of fractional order fuzzy logic controller with several evolutionary optimization algorithms for inverted pendulum
dc.contributor.author | Ghaleb, A.F. | |
dc.contributor.author | Oglah , Ahmed Alaa | |
dc.contributor.author | Humaidi, Amjad J. | |
dc.contributor.author | Al-Obaidi, Abdulkareem Sh. Mahdi | |
dc.contributor.author | Ibraheem, Ibraheem Kasim | |
dc.contributor.author | Al-Obaidi, Abdulkareem Sh. Mahdi | |
dc.contributor.status | nem | |
dc.date.accessioned | 2023-05-08T12:28:36Z | |
dc.date.available | 2023-05-08T12:28:36Z | |
dc.date.issued | 2023-02-13 | |
dc.description.abstract | This paper compared the performance between Integer Order Fuzzy PID (IOFPID) and Fractional Order Fuzzy PID (FOFPID) controllers for inverted pendulum system as a controlling plant. The parameters of each controller were tuned with four evolutionary optimization algorithms (Social Spider Optimization (SSO), Swarm Optimization (PSO), Genetic Algorithm (GA), and Particle Ant Colony Optimization (ACO)). The comparisons were carried out between the two controllers IOFPID and FOFPID, as well as among the four optimization algorithms for the two controllers. The results of comparisons proved that the FOFPID controller with SSO has achieved the best time response char- acteristics and the least tuning time. | |
dc.identifier.doi | 10.1556/1848.2021.00375 | |
dc.identifier.issn | 2062-0810 | |
dc.identifier.issue | 1 | |
dc.identifier.jtitle | International Review of Applied Sciences and Engineering | |
dc.identifier.uri | https://hdl.handle.net/2437/352252 | |
dc.identifier.url | https://akjournals.com/view/journals/1848/14/1/article-p1.xml | |
dc.identifier.volume | 14 | |
dc.language.iso | hu | |
dc.publisher | Akadémiai Kiadó | |
dc.subject | fuzzy PID | |
dc.subject | fractional order PID | |
dc.subject | GA | |
dc.subject | ACO | |
dc.subject | PSO | |
dc.subject | SSO | |
dc.title | Optimum of fractional order fuzzy logic controller with several evolutionary optimization algorithms for inverted pendulum |
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