Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization
Abstract Electric furnaces play an important role in many industrial processes where precise temperature control is essential to ensure production efficiency and product quality. Traditional proportional-integral-derivative (PID) controllers and their modified versions are commonly used to maintain...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-84085-w |
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| author | Serdar Ekinci Davut Izci Veysel Gider Laith Abualigah Mohit Bajaj Ievgen Zaitsev |
| author_facet | Serdar Ekinci Davut Izci Veysel Gider Laith Abualigah Mohit Bajaj Ievgen Zaitsev |
| author_sort | Serdar Ekinci |
| collection | DOAJ |
| description | Abstract Electric furnaces play an important role in many industrial processes where precise temperature control is essential to ensure production efficiency and product quality. Traditional proportional-integral-derivative (PID) controllers and their modified versions are commonly used to maintain temperature stability by reacting quickly to deviations. In this study, the real PID plus second-order derivative (RPIDD2) controller is introduced for the first time for industrial temperature control applications, which is a novel alternative that has not yet been investigated in the literature. To ensure optimal performance, the parameters of the RPIDD2 controller are optimized using metaheuristic algorithms, including the flood optimization algorithm (FLA), reptile search algorithm (RSA), particle swarm optimization (PSO) and differential evolution (DE). A new approach is proposed which combines the quadratic interpolation optimization (QIO) algorithm with the RPIDD2 controller, taking advantage of the fast convergence, low computational cost and high accuracy of QIO. Comparative analyses between QIO-RPIDD2, FLA-RPIDD2, RSA-RPIDD2, PSO-RPIDD2 and DE-RPIDD2 controller are performed by evaluating performance metrics such as transient and frequency response. The results show that QIO-RPIDD2 achieves superior performance, adapts quickly to different reference temperatures and performs excellently on key performance indicators. These results make the proposed QIO-RPIDD2 controller a promising solution for industrial temperature control and contribute to more efficient and adaptive optimization techniques. |
| format | Article |
| id | doaj-art-cbd9efc946834a7e88a20d03befeebd0 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-cbd9efc946834a7e88a20d03befeebd02025-01-05T12:15:24ZengNature PortfolioScientific Reports2045-23222025-01-0115111910.1038/s41598-024-84085-wEfficient control strategy for electric furnace temperature regulation using quadratic interpolation optimizationSerdar Ekinci0Davut Izci1Veysel Gider2Laith Abualigah3Mohit Bajaj4Ievgen Zaitsev5Department of Computer Engineering, Batman UniversityDepartment of Computer Engineering, Batman UniversityDistance Education Application and Researcher Center, Batman UniversityComputer Science Department, Al al-Bayt UniversityDepartment of Electrical Engineering, Graphic Era (Deemed to be University)Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of UkraineAbstract Electric furnaces play an important role in many industrial processes where precise temperature control is essential to ensure production efficiency and product quality. Traditional proportional-integral-derivative (PID) controllers and their modified versions are commonly used to maintain temperature stability by reacting quickly to deviations. In this study, the real PID plus second-order derivative (RPIDD2) controller is introduced for the first time for industrial temperature control applications, which is a novel alternative that has not yet been investigated in the literature. To ensure optimal performance, the parameters of the RPIDD2 controller are optimized using metaheuristic algorithms, including the flood optimization algorithm (FLA), reptile search algorithm (RSA), particle swarm optimization (PSO) and differential evolution (DE). A new approach is proposed which combines the quadratic interpolation optimization (QIO) algorithm with the RPIDD2 controller, taking advantage of the fast convergence, low computational cost and high accuracy of QIO. Comparative analyses between QIO-RPIDD2, FLA-RPIDD2, RSA-RPIDD2, PSO-RPIDD2 and DE-RPIDD2 controller are performed by evaluating performance metrics such as transient and frequency response. The results show that QIO-RPIDD2 achieves superior performance, adapts quickly to different reference temperatures and performs excellently on key performance indicators. These results make the proposed QIO-RPIDD2 controller a promising solution for industrial temperature control and contribute to more efficient and adaptive optimization techniques.https://doi.org/10.1038/s41598-024-84085-wQuadratic interpolation optimizationReal PID plus second-order derivative controllerTemperature controlTime responseFrequency response |
| spellingShingle | Serdar Ekinci Davut Izci Veysel Gider Laith Abualigah Mohit Bajaj Ievgen Zaitsev Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization Scientific Reports Quadratic interpolation optimization Real PID plus second-order derivative controller Temperature control Time response Frequency response |
| title | Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization |
| title_full | Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization |
| title_fullStr | Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization |
| title_full_unstemmed | Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization |
| title_short | Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization |
| title_sort | efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization |
| topic | Quadratic interpolation optimization Real PID plus second-order derivative controller Temperature control Time response Frequency response |
| url | https://doi.org/10.1038/s41598-024-84085-w |
| work_keys_str_mv | AT serdarekinci efficientcontrolstrategyforelectricfurnacetemperatureregulationusingquadraticinterpolationoptimization AT davutizci efficientcontrolstrategyforelectricfurnacetemperatureregulationusingquadraticinterpolationoptimization AT veyselgider efficientcontrolstrategyforelectricfurnacetemperatureregulationusingquadraticinterpolationoptimization AT laithabualigah efficientcontrolstrategyforelectricfurnacetemperatureregulationusingquadraticinterpolationoptimization AT mohitbajaj efficientcontrolstrategyforelectricfurnacetemperatureregulationusingquadraticinterpolationoptimization AT ievgenzaitsev efficientcontrolstrategyforelectricfurnacetemperatureregulationusingquadraticinterpolationoptimization |