Control of a Refrigeration System Benchmark Problem: An Approach based on COR Metaheuristic Algorithm and TOPSIS Method

Kagami, Ricardo Massao; Reynoso-Meza, Gilberto; Santos, Eduardo Alves Portela; Freire, Roberto Zanetti

doi:10.1016/j.ifacol.2019.09.122

Cited by 10 publications

(1 citation statement)

References 13 publications

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“…When multiple objectives are considered, conflicting objectives often appear during the problem formulation. An example of this case was addressed in [31], where the authors focused on the improvement of the system performance, trying to avoid the increase of energy consumption.…”

Section: Multiobjective Optimization Applied To Control Engineeringmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Multiobjective Optimization Applied To Control Engineeringmentioning

confidence: 99%

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

et al. 2020

Self Cite

View full text Add to dashboard Cite

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The Use of Remote Laboratories for Teaching Concepts of Energy Conversion Systems

Neto,

Alves,

de Almeida

et al. 2023

Lecture Notes in Networks and Systems

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Adaptive PID Control Strategy with Online Model Parameter Identification for Dynamic Systems: Design and Simulation

Miranda,

Cajo,

Recalde

et al. 2024

Lecture Notes in Networks and Systems

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Control of a Refrigeration System Benchmark Problem: An Approach based on COR Metaheuristic Algorithm and TOPSIS Method

Cited by 10 publications

References 13 publications

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

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

The Use of Remote Laboratories for Teaching Concepts of Energy Conversion Systems

Adaptive PID Control Strategy with Online Model Parameter Identification for Dynamic Systems: Design and Simulation

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