A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach
In control engineering education, the possibility of using a real control system in the learning process motivates professors to improve both students’ knowledge and skills, thus avoiding an approach only based on control theory. While considering that control engineering laboratories are...
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MDPI AG
2020-02-01
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| Online Access: | https://www.mdpi.com/2078-2489/11/3/132 |
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| author | Ricardo Massao Kagami Guinther Kovalski da Costa Thiago Schaedler Uhlmann Luciano Antônio Mendes Roberto Zanetti Freire |
| author_facet | Ricardo Massao Kagami Guinther Kovalski da Costa Thiago Schaedler Uhlmann Luciano Antônio Mendes Roberto Zanetti Freire |
| author_sort | Ricardo Massao Kagami |
| collection | DOAJ |
| description | In control engineering education, the possibility of using a real control system in the learning process motivates professors to improve both students’ knowledge and skills, thus avoiding an approach only based on control theory. While considering that control engineering laboratories are expensive, mainly because educational plants should reproduce classical problems that are found in the industry, the use of virtual laboratories appears as an interesting strategy for reducing costs and improving the diversity of experiments. In this research, remote experimentation was assumed regarding the ball and beam process as an alternative didactic methodology. While assuming a nonlinear and unstable open-loop process, this study presents how students should proceed to control the plant focusing on the topic that is associated with multiobjective optimization. Proportional-Integral-Derivative (PID) controller was tuned considering the Non-dominated Sorting Genetic Algorithm (NSGA-II) to illustrate the WebLab learning procedures described in this research. The proposed strategy was compared to the Åström’s robust loop shaping method to emphasize the performance of the multiobjective optimization technique. Analyzing the feedback provided by the students, remote experimentation can be seen as an interesting approach for the future of engineering learning, once it can be directly associated with industry demand of connected machines and real-time information analysis. |
| first_indexed | 2024-12-22T02:35:17Z |
| format | Article |
| id | doaj.art-038e956ed56f4a10993b2c11de11bd1b |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-12-22T02:35:17Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
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| spelling | doaj.art-038e956ed56f4a10993b2c11de11bd1b2022-12-21T18:41:47ZengMDPI AGInformation2078-24892020-02-0111313210.3390/info11030132info11030132A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization ApproachRicardo Massao Kagami0Guinther Kovalski da Costa1Thiago Schaedler Uhlmann2Luciano Antônio Mendes3Roberto Zanetti Freire4Industrial and Systems Engineering Graduate Program–PPGEPS, Polytechnic School, Pontifícia Universidade Católica do Paraná–PUCPR, Curitiba 80215-901, BrazilControl and Automation Engineering Department, Polytechnic School, Pontifícia Universidade Católica do Paraná–PUCPR, Curitiba 80215-901, BrazilIndustrial and Systems Engineering Graduate Program–PPGEPS, Polytechnic School, Pontifícia Universidade Católica do Paraná–PUCPR, Curitiba 80215-901, BrazilIndustrial and Systems Engineering Graduate Program–PPGEPS, Polytechnic School, Pontifícia Universidade Católica do Paraná–PUCPR, Curitiba 80215-901, BrazilIndustrial and Systems Engineering Graduate Program–PPGEPS, Polytechnic School, Pontifícia Universidade Católica do Paraná–PUCPR, Curitiba 80215-901, BrazilIn control engineering education, the possibility of using a real control system in the learning process motivates professors to improve both students’ knowledge and skills, thus avoiding an approach only based on control theory. While considering that control engineering laboratories are expensive, mainly because educational plants should reproduce classical problems that are found in the industry, the use of virtual laboratories appears as an interesting strategy for reducing costs and improving the diversity of experiments. In this research, remote experimentation was assumed regarding the ball and beam process as an alternative didactic methodology. While assuming a nonlinear and unstable open-loop process, this study presents how students should proceed to control the plant focusing on the topic that is associated with multiobjective optimization. Proportional-Integral-Derivative (PID) controller was tuned considering the Non-dominated Sorting Genetic Algorithm (NSGA-II) to illustrate the WebLab learning procedures described in this research. The proposed strategy was compared to the Åström’s robust loop shaping method to emphasize the performance of the multiobjective optimization technique. Analyzing the feedback provided by the students, remote experimentation can be seen as an interesting approach for the future of engineering learning, once it can be directly associated with industry demand of connected machines and real-time information analysis.https://www.mdpi.com/2078-2489/11/3/132virtual laboratoriesmultiobjective optimizationcontrol engineering educationadvanced controlball and beam process |
| spellingShingle | Ricardo Massao Kagami Guinther Kovalski da Costa Thiago Schaedler Uhlmann Luciano Antônio Mendes Roberto Zanetti Freire A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach Information virtual laboratories multiobjective optimization control engineering education advanced control ball and beam process |
| title | A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach |
| title_full | A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach |
| title_fullStr | A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach |
| title_full_unstemmed | A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach |
| title_short | A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach |
| title_sort | generic weblab control tuning experience using the ball and beam process and multiobjective optimization approach |
| topic | virtual laboratories multiobjective optimization control engineering education advanced control ball and beam process |
| url | https://www.mdpi.com/2078-2489/11/3/132 |
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