Fuzzy multi-model based dynamic sliding mode control for chemical process with long-time delay
The chemical process industry frequently encounters uncertainties, disturbances, and varying operational demands, necessitating robust control strategies to ensure safety, efficiency, and optimal performance. In addition, the non-linearities inherent in chemical processes complicate control efforts,...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025002798 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832087427033858048 |
|---|---|
| author | Marco Herrera Oscar Camacho Alvaro Prado |
| author_facet | Marco Herrera Oscar Camacho Alvaro Prado |
| author_sort | Marco Herrera |
| collection | DOAJ |
| description | The chemical process industry frequently encounters uncertainties, disturbances, and varying operational demands, necessitating robust control strategies to ensure safety, efficiency, and optimal performance. In addition, the non-linearities inherent in chemical processes complicate control efforts, as system behavior can vary significantly under different operating conditions. This paper presents the development and application of a Fuzzy Multi-Model Control (FMMC) system designed to manage chemical processes with long time delays at various operating points. The Takagi-Sugeno (T-S) fuzzy modeling approach, where each fuzzy rule represents a local linear system, is integrated with Dynamic Sliding Mode Control (DSMC) to enhance robustness and control performance under these varying conditions. To ensure the accuracy of the system's dynamics and provide a solid foundation for the proposed control strategy, the modeling was validated using the mean squared error (MSE). The parameters of the proposed controller were determined using Particle Swarm Optimization techniques (PSO), which optimize the effectiveness of the controller. The controller employs fuzzy switching, resulting in a streamlined DSMC formulation that effectively adapts to changes in the dynamic process. The results of the thermal processes performed in real-time experiments showed that the proposed controller not only maintained control within the operational range but also reduced the impact of disturbances and uncertainties. Moreover, its performance was validated using the indices IAE, ISE, and TVu, highlighting its suitability as an excellent solution for dynamic and uncertain conditions in the chemical process industry. |
| format | Article |
| id | doaj-art-dbb86f09ee2e4031af532f018c2a30a2 |
| institution | Kabale University |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-dbb86f09ee2e4031af532f018c2a30a22025-02-06T05:12:42ZengElsevierResults in Engineering2590-12302025-03-0125104193Fuzzy multi-model based dynamic sliding mode control for chemical process with long-time delayMarco Herrera0Oscar Camacho1Alvaro Prado2Departamento de Ingeniería de Sistemas y Computación (DISC), Universidad Católica del Norte (UCN), Antofagasta 1270709, Chile; Colegio de Ciencias e Ingenierías, Universidad San Francisco de Quito USFQ, Quito 170157, EcuadorColegio de Ciencias e Ingenierías, Universidad San Francisco de Quito USFQ, Quito 170157, EcuadorDepartamento de Ingeniería de Sistemas y Computación (DISC), Universidad Católica del Norte (UCN), Antofagasta 1270709, Chile; Corresponding author.The chemical process industry frequently encounters uncertainties, disturbances, and varying operational demands, necessitating robust control strategies to ensure safety, efficiency, and optimal performance. In addition, the non-linearities inherent in chemical processes complicate control efforts, as system behavior can vary significantly under different operating conditions. This paper presents the development and application of a Fuzzy Multi-Model Control (FMMC) system designed to manage chemical processes with long time delays at various operating points. The Takagi-Sugeno (T-S) fuzzy modeling approach, where each fuzzy rule represents a local linear system, is integrated with Dynamic Sliding Mode Control (DSMC) to enhance robustness and control performance under these varying conditions. To ensure the accuracy of the system's dynamics and provide a solid foundation for the proposed control strategy, the modeling was validated using the mean squared error (MSE). The parameters of the proposed controller were determined using Particle Swarm Optimization techniques (PSO), which optimize the effectiveness of the controller. The controller employs fuzzy switching, resulting in a streamlined DSMC formulation that effectively adapts to changes in the dynamic process. The results of the thermal processes performed in real-time experiments showed that the proposed controller not only maintained control within the operational range but also reduced the impact of disturbances and uncertainties. Moreover, its performance was validated using the indices IAE, ISE, and TVu, highlighting its suitability as an excellent solution for dynamic and uncertain conditions in the chemical process industry.http://www.sciencedirect.com/science/article/pii/S2590123025002798Fuzzy multi-modelTakagi-Sugeno modelingDynamic sliding mode controlChemical processesLong time delay |
| spellingShingle | Marco Herrera Oscar Camacho Alvaro Prado Fuzzy multi-model based dynamic sliding mode control for chemical process with long-time delay Results in Engineering Fuzzy multi-model Takagi-Sugeno modeling Dynamic sliding mode control Chemical processes Long time delay |
| title | Fuzzy multi-model based dynamic sliding mode control for chemical process with long-time delay |
| title_full | Fuzzy multi-model based dynamic sliding mode control for chemical process with long-time delay |
| title_fullStr | Fuzzy multi-model based dynamic sliding mode control for chemical process with long-time delay |
| title_full_unstemmed | Fuzzy multi-model based dynamic sliding mode control for chemical process with long-time delay |
| title_short | Fuzzy multi-model based dynamic sliding mode control for chemical process with long-time delay |
| title_sort | fuzzy multi model based dynamic sliding mode control for chemical process with long time delay |
| topic | Fuzzy multi-model Takagi-Sugeno modeling Dynamic sliding mode control Chemical processes Long time delay |
| url | http://www.sciencedirect.com/science/article/pii/S2590123025002798 |
| work_keys_str_mv | AT marcoherrera fuzzymultimodelbaseddynamicslidingmodecontrolforchemicalprocesswithlongtimedelay AT oscarcamacho fuzzymultimodelbaseddynamicslidingmodecontrolforchemicalprocesswithlongtimedelay AT alvaroprado fuzzymultimodelbaseddynamicslidingmodecontrolforchemicalprocesswithlongtimedelay |