Designing multivariable PI controller with multi-response optimization for a pilot plant binary distillation column: a robust design approach
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| Pubblicato in: | Journal of Engineering, Design and Technology vol. 23, no. 1 (2025), p. 207-227 |
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| 024 | 7 | |a 10.1108/JEDT-12-2022-0616 |2 doi | |
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| 045 | 2 | |b d20250101 |b d20250228 | |
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| 100 | 1 | |a Bhat, Vinayambika S |u Department of Electronics and Communication Engineering, Mangalore Institute of Technology and Engineering, Moodabidre, India | |
| 245 | 1 | |a Designing multivariable PI controller with multi-response optimization for a pilot plant binary distillation column: a robust design approach | |
| 260 | |b Emerald Group Publishing Limited |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a PurposeThe purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.Design/methodology/approachTaguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.FindingsResearch indicates that integral control parameters (Ki) affect outputs substantially more than proportional control parameters (Kp). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.Originality/valueThis paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve. | |
| 653 | |a Time lag | ||
| 653 | |a Pilot plants | ||
| 653 | |a Systems design | ||
| 653 | |a Parameter robustness | ||
| 653 | |a Environmental impact | ||
| 653 | |a Time constant | ||
| 653 | |a Research & development--R&D | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Industrial electronics | ||
| 653 | |a Transfer functions | ||
| 653 | |a Simulation | ||
| 653 | |a Robust control | ||
| 653 | |a Control algorithms | ||
| 653 | |a Noise control | ||
| 653 | |a Control systems design | ||
| 653 | |a Sustainable development | ||
| 653 | |a Proportional integral | ||
| 653 | |a Proportional control | ||
| 653 | |a Robust design | ||
| 653 | |a Process controls | ||
| 653 | |a Controllers | ||
| 653 | |a Consumption | ||
| 653 | |a Distillation | ||
| 653 | |a Design | ||
| 653 | |a Algorithms | ||
| 653 | |a Controllability | ||
| 653 | |a Multivariable control | ||
| 653 | |a Performance indices | ||
| 653 | |a Real time | ||
| 653 | |a Design optimization | ||
| 653 | |a Process engineering | ||
| 653 | |a Design engineering | ||
| 700 | 1 | |a Thirunavukkarasu Indiran |u Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal, India | |
| 700 | 1 | |a Selvanathan, Shanmuga Priya |u Department of Chemical Engineering, Manipal Institute of Technology, Manipal, India, and | |
| 700 | 1 | |a Bhat, Shreeranga |u Department of Mechanical Engineeing, St Joseph Engineering College, Mangalore, India | |
| 773 | 0 | |t Journal of Engineering, Design and Technology |g vol. 23, no. 1 (2025), p. 207-227 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3150634877/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3150634877/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3150634877/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |