References of "Hernandez, Andres"
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See detailNonlinear identification and control of Organic Rankine Cycle systems using sparse polynomial models
Hernandez, Andres; Ruiz, Fredy; Ionescu, Clara et al

in Proceedings of the 2016 IEEE Conference on Control Applications (CCA) Part of 2016 IEEE Multi-Conference on Systems and Contro (2016, September 19)

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 ... [more ▼]

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. [less ▲]

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See detailSteady-state and dynamic validation of a small scale waste heat recovery system using the ThermoCycle Modelica library
Desideri, Adriano ULiege; Hernandez, Andres; Gusev, Sergei et al

in Energy (2016), 115

The organic Rankine cycle (ORC) power system has been recognized as a promising technology for micro power applications. In this context, physics-based dynamic models can constitute a significant tool for ... [more ▼]

The organic Rankine cycle (ORC) power system has been recognized as a promising technology for micro power applications. In this context, physics-based dynamic models can constitute a significant tool for the further development of the technology, allowing to evaluate and optimize response times during transients, or to implement and test innovative control strategies. In this contribution, the dynamic model of an ORC power unit based on the ThermoCycle Modelica library is validated against steady-state and transient experimental results from an 11 kWel stationary ORC system. The simulation results are in good agreement with the measurements, both in steady-state and in transient conditions. The validated library is readily usable to investigate demanding dynamics-based problems for low capacity power systems. [less ▲]

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See detailDYNAMIC MODELING OF WASTE HEAT RECOVERY ORGANIC RANKINE CYCLE SYSTEMS IN THE AMESIM PLATFORM
Guillaume, Ludovic ULiege; Ameel, Bernd; Criens, Chris et al

Conference (2016, September 14)

ORC waste heat recovery is a very promising technology for reducing fuel consumption and consequently the CO2 emissions of future heavy-duty trucks. Because of the transient nature of the heat sources ... [more ▼]

ORC waste heat recovery is a very promising technology for reducing fuel consumption and consequently the CO2 emissions of future heavy-duty trucks. Because of the transient nature of the heat sources encountered on a truck, dynamic simulations are an essential part of the design process of ORC systems for truck applications. Dynamic models are useful for component design, control design and transient evaluation of ORC systems. To ease the burden of building numerous dynamic models of different candidate ORCs while the design process is ongoing, a library of generic dynamic models of ORCs is built in this work. These models work in synergy with a steady-state ORC design tool in which is added a function to automatically populate the parameters of the dynamic models. In this work, the dynamic model library and their parameterization process in LMS AMESim are described. The platform is largely used in automotive industry and offers a variety of libraries: Engine, Control, Two-Phase Flow, etc. Finally, the dynamic models are compared against the steady-state models and experimental data. [less ▲]

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See detailIBISCA-Panama, a large-scale study of arthropod beta-diversity and vertical stratification in a lowland rainforest: rationale, description of study sites and field methodology
Basset, Yves; Corbara, Bruno; Barrios, Hector et al

in Bulletin de l'Institut Royal des Sciences Naturelles de Belgique. Entomologie (2007), 77

Detailed reference viewed: 45 (4 ULiège)