Evaluating the ANN Model Performance for PID Controller Tuning in Flow Process Control: A Comparative Study
Accurate controller tuning is important for ensuring optimal performance in flow control processes, particularly onboard ships, where precise control of fluid systems such as oil, gas, and water flows determines the operation of the whole ship. Models can be used to avoid experimentation on a real s...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/11006639/ |
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| author | Nur Assani Petar Matic |
| author_facet | Nur Assani Petar Matic |
| author_sort | Nur Assani |
| collection | DOAJ |
| description | Accurate controller tuning is important for ensuring optimal performance in flow control processes, particularly onboard ships, where precise control of fluid systems such as oil, gas, and water flows determines the operation of the whole ship. Models can be used to avoid experimentation on a real system, which is essential if systems are unavailable for controller tuning experiments. This paper presents the results of controller tuning using the ANN model. To evaluate the effectiveness of the proposed method, it is compared to the transfer function model-based tuning and to the controller tuning performed on a real system. The controller uses an ideal PID structure, and controller parameters are calculated by four well-known tuning methods for each case. The experiments are conducted on a flow control unit in a laboratory, while modelling and simulations are performed in Matlab. Graphical evaluation and numerical RMSE metrics are used to determine the quality of the tuning method. By evaluating controller tuning performance based on the ANN model, this research aims to validate the effectiveness of ANN models for practical control applications. |
| format | Article |
| id | doaj-art-e02835adf5114a49b455aa4672fc668a |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-e02835adf5114a49b455aa4672fc668a2025-08-20T01:53:04ZengIEEEIEEE Access2169-35362025-01-0113884998850810.1109/ACCESS.2025.357122211006639Evaluating the ANN Model Performance for PID Controller Tuning in Flow Process Control: A Comparative StudyNur Assani0https://orcid.org/0000-0003-0427-5186Petar Matic1https://orcid.org/0000-0002-1799-5257Faculty of Maritime Studies, University of Split, Split, CroatiaFaculty of Maritime Studies, University of Split, Split, CroatiaAccurate controller tuning is important for ensuring optimal performance in flow control processes, particularly onboard ships, where precise control of fluid systems such as oil, gas, and water flows determines the operation of the whole ship. Models can be used to avoid experimentation on a real system, which is essential if systems are unavailable for controller tuning experiments. This paper presents the results of controller tuning using the ANN model. To evaluate the effectiveness of the proposed method, it is compared to the transfer function model-based tuning and to the controller tuning performed on a real system. The controller uses an ideal PID structure, and controller parameters are calculated by four well-known tuning methods for each case. The experiments are conducted on a flow control unit in a laboratory, while modelling and simulations are performed in Matlab. Graphical evaluation and numerical RMSE metrics are used to determine the quality of the tuning method. By evaluating controller tuning performance based on the ANN model, this research aims to validate the effectiveness of ANN models for practical control applications.https://ieeexplore.ieee.org/document/11006639/Artificial neural networkscontroller tuningflow processmodelingPID control |
| spellingShingle | Nur Assani Petar Matic Evaluating the ANN Model Performance for PID Controller Tuning in Flow Process Control: A Comparative Study IEEE Access Artificial neural networks controller tuning flow process modeling PID control |
| title | Evaluating the ANN Model Performance for PID Controller Tuning in Flow Process Control: A Comparative Study |
| title_full | Evaluating the ANN Model Performance for PID Controller Tuning in Flow Process Control: A Comparative Study |
| title_fullStr | Evaluating the ANN Model Performance for PID Controller Tuning in Flow Process Control: A Comparative Study |
| title_full_unstemmed | Evaluating the ANN Model Performance for PID Controller Tuning in Flow Process Control: A Comparative Study |
| title_short | Evaluating the ANN Model Performance for PID Controller Tuning in Flow Process Control: A Comparative Study |
| title_sort | evaluating the ann model performance for pid controller tuning in flow process control a comparative study |
| topic | Artificial neural networks controller tuning flow process modeling PID control |
| url | https://ieeexplore.ieee.org/document/11006639/ |
| work_keys_str_mv | AT nurassani evaluatingtheannmodelperformanceforpidcontrollertuninginflowprocesscontrolacomparativestudy AT petarmatic evaluatingtheannmodelperformanceforpidcontrollertuninginflowprocesscontrolacomparativestudy |