Toward Optimal Control of a Multivariable Magnetic Levitation System
In the paper, a comparative case study covering different control strategies of unstable and nonlinear magnetic levitation process is investigated. Three control procedures are examined in order to fulfill the specified performance indices. Thus, a dedicated PD regulator along with the hybrid fuzzy...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/2/674 |
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| author | Paweł Majewski Dawid Pawuś Krzysztof Szurpicki Wojciech P. Hunek |
| author_facet | Paweł Majewski Dawid Pawuś Krzysztof Szurpicki Wojciech P. Hunek |
| author_sort | Paweł Majewski |
| collection | DOAJ |
| description | In the paper, a comparative case study covering different control strategies of unstable and nonlinear magnetic levitation process is investigated. Three control procedures are examined in order to fulfill the specified performance indices. Thus, a dedicated PD regulator along with the hybrid fuzzy logic PID one as well as feed-forward neural network regulator are respected and summarized according to generally understood tuning techniques. It should be emphasized that the second PID controller is strictly derived from both arbitrary chosen membership functions and those ones selected through the genetic algorithm mechanism. Simulation examples have successfully confirmed the correctness of obtained results, especially in terms of entire control process quality of the magnetic levitation system. It has been observed that the artificial-intelligence-originated approaches have outperformed the classical one in the context of control accuracy and control speed properties in contrary to the energy-saving behavior whereby the conventional method has become a leader. The feature-related compromise, which has never been seen before, along with other crucial peculiarities, is effectively discussed within this paper. |
| first_indexed | 2024-03-10T01:59:11Z |
| format | Article |
| id | doaj.art-c3c5cecea49b4e4c8d16947bfdd88532 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T01:59:11Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-c3c5cecea49b4e4c8d16947bfdd885322023-11-23T12:50:52ZengMDPI AGApplied Sciences2076-34172022-01-0112267410.3390/app12020674Toward Optimal Control of a Multivariable Magnetic Levitation SystemPaweł Majewski0Dawid Pawuś1Krzysztof Szurpicki2Wojciech P. Hunek3Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76 Street, 45-758 Opole, PolandFaculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76 Street, 45-758 Opole, PolandFaculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76 Street, 45-758 Opole, PolandFaculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76 Street, 45-758 Opole, PolandIn the paper, a comparative case study covering different control strategies of unstable and nonlinear magnetic levitation process is investigated. Three control procedures are examined in order to fulfill the specified performance indices. Thus, a dedicated PD regulator along with the hybrid fuzzy logic PID one as well as feed-forward neural network regulator are respected and summarized according to generally understood tuning techniques. It should be emphasized that the second PID controller is strictly derived from both arbitrary chosen membership functions and those ones selected through the genetic algorithm mechanism. Simulation examples have successfully confirmed the correctness of obtained results, especially in terms of entire control process quality of the magnetic levitation system. It has been observed that the artificial-intelligence-originated approaches have outperformed the classical one in the context of control accuracy and control speed properties in contrary to the energy-saving behavior whereby the conventional method has become a leader. The feature-related compromise, which has never been seen before, along with other crucial peculiarities, is effectively discussed within this paper.https://www.mdpi.com/2076-3417/12/2/674magnetic levitation processfuzzy logicneural networkartificial intelligencegenetic algorithmpractical scheme |
| spellingShingle | Paweł Majewski Dawid Pawuś Krzysztof Szurpicki Wojciech P. Hunek Toward Optimal Control of a Multivariable Magnetic Levitation System Applied Sciences magnetic levitation process fuzzy logic neural network artificial intelligence genetic algorithm practical scheme |
| title | Toward Optimal Control of a Multivariable Magnetic Levitation System |
| title_full | Toward Optimal Control of a Multivariable Magnetic Levitation System |
| title_fullStr | Toward Optimal Control of a Multivariable Magnetic Levitation System |
| title_full_unstemmed | Toward Optimal Control of a Multivariable Magnetic Levitation System |
| title_short | Toward Optimal Control of a Multivariable Magnetic Levitation System |
| title_sort | toward optimal control of a multivariable magnetic levitation system |
| topic | magnetic levitation process fuzzy logic neural network artificial intelligence genetic algorithm practical scheme |
| url | https://www.mdpi.com/2076-3417/12/2/674 |
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