Nonlinear identification and control of organic rankine cycle systems using sparse polynomial models
- Author
- Jairo Andres Hernandez Naranjo (UGent) , Fredy Ruiz, Adriano Desideri, Clara Ionescu (UGent) , Sylvain Quoilin, Vincent Lemort and Robain De Keyser (UGent)
- Organization
- Abstract
- Development of a first principles model of a system is not only a time-and cost-consuming task, but often leads to model structures which are not directly usable to design a controller using current available methodologies. In this paper we use a sparse identification procedure to obtain a nonlinear polynomial model. Since this is a NP-hard problem, a relaxed algorithm is employed to accelerate its convergence speed. The obtained model is further used inside the nonlinear Extended Prediction Self-Adaptive control (NEPSAC) approach to Nonlinear Model Predictive Control (NMPC), which replaces the complex nonlinear optimization problem by a simpler iterative quadratic programming procedure. An organic Rankine cycle system, characterized for presenting nonlinear time-varying dynamics, is used as benchmark to illustrate the effectiveness of the proposed combined strategies.
- Keywords
- SELECTION, ENGINE
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8113786
- MLA
- Hernandez Naranjo, Jairo Andres, et al. “Nonlinear Identification and Control of Organic Rankine Cycle Systems Using Sparse Polynomial Models.” 2016 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA), 2016, pp. 1012–17.
- APA
- Hernandez Naranjo, J. A., Ruiz, F., Desideri, A., Ionescu, C., Quoilin, S., Lemort, V., & De Keyser, R. (2016). Nonlinear identification and control of organic rankine cycle systems using sparse polynomial models. 2016 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA), 1012–1017.
- Chicago author-date
- Hernandez Naranjo, Jairo Andres, Fredy Ruiz, Adriano Desideri, Clara Ionescu, Sylvain Quoilin, Vincent Lemort, and Robain De Keyser. 2016. “Nonlinear Identification and Control of Organic Rankine Cycle Systems Using Sparse Polynomial Models.” In 2016 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA), 1012–17.
- Chicago author-date (all authors)
- Hernandez Naranjo, Jairo Andres, Fredy Ruiz, Adriano Desideri, Clara Ionescu, Sylvain Quoilin, Vincent Lemort, and Robain De Keyser. 2016. “Nonlinear Identification and Control of Organic Rankine Cycle Systems Using Sparse Polynomial Models.” In 2016 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA), 1012–1017.
- Vancouver
- 1.Hernandez Naranjo JA, Ruiz F, Desideri A, Ionescu C, Quoilin S, Lemort V, et al. Nonlinear identification and control of organic rankine cycle systems using sparse polynomial models. In: 2016 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA). 2016. p. 1012–7.
- IEEE
- [1]J. A. Hernandez Naranjo et al., “Nonlinear identification and control of organic rankine cycle systems using sparse polynomial models,” in 2016 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA), Buenos Aires, Argentina, 2016, pp. 1012–1017.
@inproceedings{8113786,
abstract = {{Development of a first principles model of a system is not only a time-and cost-consuming task, but often leads to model structures which are not directly usable to design a controller using current available methodologies. In this paper we use a sparse identification procedure to obtain a nonlinear polynomial model. Since this is a NP-hard problem, a relaxed algorithm is employed to accelerate its convergence speed. The obtained model is further used inside the nonlinear Extended Prediction Self-Adaptive control (NEPSAC) approach to Nonlinear Model Predictive Control (NMPC), which replaces the complex nonlinear optimization problem by a simpler iterative quadratic programming procedure. An organic Rankine cycle system, characterized for presenting nonlinear time-varying dynamics, is used as benchmark to illustrate the effectiveness of the proposed combined strategies.}},
author = {{Hernandez Naranjo, Jairo Andres and Ruiz, Fredy and Desideri, Adriano and Ionescu, Clara and Quoilin, Sylvain and Lemort, Vincent and De Keyser, Robain}},
booktitle = {{2016 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA)}},
isbn = {{978-1-5090-0755-4}},
issn = {{1085-1992}},
keywords = {{SELECTION,ENGINE}},
language = {{eng}},
location = {{Buenos Aires, Argentina}},
pages = {{1012--1017}},
title = {{Nonlinear identification and control of organic rankine cycle systems using sparse polynomial models}},
year = {{2016}},
}