Reference : Nonlinear identification and control of Organic Rankine Cycle systems using sparse po...
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Energy
http://hdl.handle.net/2268/205798
Nonlinear identification and control of Organic Rankine Cycle systems using sparse polynomial models
English
Hernandez, Andres [Universiteit Gent - Ugent > Electrical Energy, Systems and Automation > > PhD student >]
Ruiz, Fredy [Pontificia Universidad Javeriana, Colombia > Electronics Engineering > > Researcher >]
Ionescu, Clara [Universiteit Gent - Ugent > Electrical Energy Systems and Automation > > Senior Researcher >]
Quoilin, Sylvain mailto [Université de Liège > Département d'aérospatiale et mécanique > Systèmes énergétiques >]
Lemort, Vincent mailto [Université de Liège > Département d'aérospatiale et mécanique > Systèmes énergétiques >]
De Keyser, Robin [Universiteit Gent - Ugent > Electrical energym systems and automation > > Full Professor >]
Desideri, Adriano mailto [Université de Liège > Département d'aérospatiale et mécanique > Systèmes énergétiques >]
19-Sep-2016
Proceedings of the 2016 IEEE Conference on Control Applications (CCA) Part of 2016 IEEE Multi-Conference on Systems and Contro
Yes
2016 IEEE Conference on Control Applications (CCA) Part of 2016 IEEE Multi-Conference on Systems and Contro
from 19-09-2016 to 22-09-2016
[en] 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 Non- linear 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.
http://hdl.handle.net/2268/205798

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
Hernandez - 2016 - Nonlinear identification and control of organic Rankine cycle systems using sparse polynomial models.pdfPublisher postprint306.06 kBView/Open

Bookmark and Share SFX Query

All documents in ORBi are protected by a user license.