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Open AccessArticle

A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach

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Industrial and Systems Engineering Graduate Program–PPGEPS, Polytechnic School, Pontifícia Universidade Católica do Paraná–PUCPR, Curitiba 80215-901, Brazil
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Control and Automation Engineering Department, Polytechnic School, Pontifícia Universidade Católica do Paraná–PUCPR, Curitiba 80215-901, Brazil
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Authors to whom correspondence should be addressed.
Information 2020, 11(3), 132; https://doi.org/10.3390/info11030132
Received: 31 December 2019 / Revised: 20 February 2020 / Accepted: 24 February 2020 / Published: 27 February 2020
(This article belongs to the Special Issue Online Experimentation and the IoE)
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. View Full-Text
Keywords: virtual laboratories; multiobjective optimization; control engineering education; advanced control; ball and beam process virtual laboratories; multiobjective optimization; control engineering education; advanced control; ball and beam process
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Kagami, R.M.; da Costa, G.K.; Uhlmann, T.S.; Mendes, L.A.; Freire, R.Z. A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach. Information 2020, 11, 132.

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