Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice
En este artículo se presenta un enfoque para la sintonización de un control predictivo no lineal basado en modelos (NMPC). (NMPC) basado en modelos. El control propuesto utiliza el algoritmo de optimización de búsqueda de patrones (PSM), que se aplica al control no lineal del pH en el proceso de alc...
- Autores:
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2021
- Institución:
- Universidad de Bogotá Jorge Tadeo Lozano
- Repositorio:
- Expeditio: repositorio UTadeo
- Idioma:
- spa
- OAI Identifier:
- oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/32269
- Palabra clave:
- Alcalinización
Control no lineal
Optimización
- Rights
- License
- Abierto (Texto Completo)
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Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice |
| title |
Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice |
| spellingShingle |
Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice Alcalinización Control no lineal Optimización |
| title_short |
Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice |
| title_full |
Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice |
| title_fullStr |
Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice |
| title_full_unstemmed |
Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice |
| title_sort |
Optimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar Juice |
| dc.subject.spa.fl_str_mv |
Alcalinización Control no lineal |
| topic |
Alcalinización Control no lineal Optimización |
| dc.subject.lemb.spa.fl_str_mv |
Optimización |
| description |
En este artículo se presenta un enfoque para la sintonización de un control predictivo no lineal basado en modelos (NMPC). (NMPC) basado en modelos. El control propuesto utiliza el algoritmo de optimización de búsqueda de patrones (PSM), que se aplica al control no lineal del pH en el proceso de alcalinización del zumo de azúcar. En primer lugar, la En primer lugar, la identificación del modelo se realiza utilizando los sistemas de inferencia difusa T-S de Takagi Sugeno con conjuntos difusos multidimensionales. El siguiente paso es el ajuste de los parámetros del controlador. En ambos casos se utiliza el algoritmo PSM. ambos casos. El enfoque propuesto permite minimizar la incertidumbre del modelo y disminuir en la respuesta, el error en estado estacionario cuando se compara con otros autores que realizan el mismo procedimiento pero aplican otros algoritmos de optimización. Los resultados muestran una mejora en el error en estado estacionario en la respuesta de la planta. |
| publishDate |
2021 |
| dc.date.created.none.fl_str_mv |
2021 |
| dc.date.accessioned.none.fl_str_mv |
2023-10-31T04:57:34Z |
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2023-10-31T04:57:34Z |
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http://purl.org/coar/resource_type/c_6501 |
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http://purl.org/coar/resource_type/c_6501 |
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https://www.mdpi.com/2227-9717/9/12/2283 |
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http://hdl.handle.net/20.500.12010/32269 |
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https://www.mdpi.com/2227-9717/9/12/2283 http://hdl.handle.net/20.500.12010/32269 |
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spa |
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spa |
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Kasi, A.; Velagi, J.; Osmanovi, A. Design of NMPC-Based Framework for Mobile Robot Motion in Unstructured Environments. In Proceedings of the 2018 International Symposium ELMAR, Zadar, Croatia, 16–19 September 2018; pp. 183–186. Roy, K.; Bhati, J.; Paruya, S. Evaluating Successive Linearization in NMPC for Controlling Oscillations in Boiling Channel. In Proceedings of the 18th International Conference on Control, Automation and Systems (ICCAS), Institute of Control, Robotics and Systems–ICROS, PyeongChang, Korea, 17–20 October 2018; pp. 1260–1264. Gros, S.; Quirynen, R.; Diehl, M. An Improved Real-time Economic NMPC Scheme for Wind Turbine Control Using Spline- Interpolated Aerodynamic Coefficients. In Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, CA, USA, 15–17 December 2014. [CrossRef] Guo, N.; Lenzo, B.; Zhang, X.; Zou, Y.; Zhai, R.; Zhang, T. A Real-Time Nonlinear Model Predictive Controller for Yaw Motion Optimization of Distributed Drive Electric Vehicles. IEEE Trans. Veh. Technol. 2020, 69, 4935–4946. [CrossRef] Herrera, J.; Ibeas, A.; Alcántara, S.; Vilanova, R. Identification and adaptive control of delayed unstable systems. In Proceedings of the 2010 IEEE International Symposium on Intelligent Control, Yokohama, Japan, 8–10 September 2010; pp. 767–772. [CrossRef] Lemonge, A.; Barbosa, H. A new adaptive penalty scheme for genetic algorithms. Inf. Sci. 2003, 3, 215–251. Schutte, J.; Groenwold, A. Sizing design of truss structures using particle swarms. Struct. Multidiscip. Optim. 2003, 25, 261–269. [CrossRef] |
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Abierto (Texto Completo) |
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Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
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16 páginas |
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Processes |
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Universidad de Bogotá Jorge Tadeo Lozano |
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2023-10-31T04:57:34Z2023-10-31T04:57:34Z2021https://www.mdpi.com/2227-9717/9/12/2283http://hdl.handle.net/20.500.12010/32269En este artículo se presenta un enfoque para la sintonización de un control predictivo no lineal basado en modelos (NMPC). (NMPC) basado en modelos. El control propuesto utiliza el algoritmo de optimización de búsqueda de patrones (PSM), que se aplica al control no lineal del pH en el proceso de alcalinización del zumo de azúcar. En primer lugar, la En primer lugar, la identificación del modelo se realiza utilizando los sistemas de inferencia difusa T-S de Takagi Sugeno con conjuntos difusos multidimensionales. El siguiente paso es el ajuste de los parámetros del controlador. En ambos casos se utiliza el algoritmo PSM. ambos casos. El enfoque propuesto permite minimizar la incertidumbre del modelo y disminuir en la respuesta, el error en estado estacionario cuando se compara con otros autores que realizan el mismo procedimiento pero aplican otros algoritmos de optimización. Los resultados muestran una mejora en el error en estado estacionario en la respuesta de la planta.#OptimizaciónIn this paper, an approach for the tuning of a model-based non-linear predictive control (NMPC) is presented. The proposed control uses the pattern search optimization algorithm (PSM), which is applied to the pH non-linear control in the alkalinization process of sugar juice. First, the model identification is made using the Takagi Sugeno T-S fuzzy inference systems with multidimensional fuzzy sets; the next step is the controller parameters tuning. The PSM algorithm is used in both cases. The proposed approach allows the minimization of model uncertainty and decreases, in the response, the error in a steady state when compared with other authors who perform the same procedure but apply other optimization algorithms. The results show an improvement in the steady-state error in the plant response.16 páginasapplication/pdfspaProcessesAlcalinizaciónControl no linealOptimizaciónOptimization Based on Pattern Search Algorithm Applied to pH Non-Linear Control: Application to Alkalinization Process of Sugar JuiceAbierto (Texto Completo)http://purl.org/coar/access_right/c_abf2Kasi, A.; Velagi, J.; Osmanovi, A. Design of NMPC-Based Framework for Mobile Robot Motion in Unstructured Environments. In Proceedings of the 2018 International Symposium ELMAR, Zadar, Croatia, 16–19 September 2018; pp. 183–186.Roy, K.; Bhati, J.; Paruya, S. Evaluating Successive Linearization in NMPC for Controlling Oscillations in Boiling Channel. In Proceedings of the 18th International Conference on Control, Automation and Systems (ICCAS), Institute of Control, Robotics and Systems–ICROS, PyeongChang, Korea, 17–20 October 2018; pp. 1260–1264.Gros, S.; Quirynen, R.; Diehl, M. An Improved Real-time Economic NMPC Scheme for Wind Turbine Control Using Spline- Interpolated Aerodynamic Coefficients. In Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, CA, USA, 15–17 December 2014. [CrossRef]Guo, N.; Lenzo, B.; Zhang, X.; Zou, Y.; Zhai, R.; Zhang, T. A Real-Time Nonlinear Model Predictive Controller for Yaw Motion Optimization of Distributed Drive Electric Vehicles. IEEE Trans. Veh. Technol. 2020, 69, 4935–4946. [CrossRef]Herrera, J.; Ibeas, A.; Alcántara, S.; Vilanova, R. Identification and adaptive control of delayed unstable systems. In Proceedings of the 2010 IEEE International Symposium on Intelligent Control, Yokohama, Japan, 8–10 September 2010; pp. 767–772. [CrossRef]Lemonge, A.; Barbosa, H. A new adaptive penalty scheme for genetic algorithms. Inf. Sci. 2003, 3, 215–251.Schutte, J.; Groenwold, A. Sizing design of truss structures using particle swarms. Struct. Multidiscip. Optim. 2003, 25, 261–269. [CrossRef]http://purl.org/coar/resource_type/c_6501Palacio-Morales, JairoTobón, AndrésHerrera, JorgeORIGINALprocesses-09-02283.pdfprocesses-09-02283.pdfapplication/pdf758196https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/32269/1/processes-09-02283.pdf5b6cfa57d209ed24ada0796f31ace9adMD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/32269/2/license.txtbaba314677a6b940f072575a13bb6906MD52open accessTHUMBNAILprocesses-09-02283.pdf.jpgprocesses-09-02283.pdf.jpgIM Thumbnailimage/jpeg21342https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/32269/3/processes-09-02283.pdf.jpgd90664095d7aafb06dd0c17581862743MD53open access20.500.12010/32269oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/322692023-11-10 10:05:55.934open accessRepositorio Institucional - Universidad Jorge Tadeo Lozanoexpeditiorepositorio@utadeo.edu.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 |