Search Results - "R. Ramírez, Daniel"

Estimación de intensidades rotóricas en máquinas polifásicas para control predictivo by G. Satué, Manuel, R. Arahal, Manuel, R. Ramírez, Daniel

“…El control predictivo de corrientes de estátor precisa una estimación de las corrientes rotóricas que son, usualmente, no medibles. Estas corrientes afectan a…”
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Real-Time Implementation of a Constrained MPC for Efficient Airflow Control in a PEM Fuel Cell by Arce, Alicia, del Real, Alejandro J, Bordons, Carlos, Ramirez, Daniel R

“…Fuel cells represent an area of great industrial interest due to the possibility to generate clean energy for stationary and automotive applications. It is…”
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Stock Forecasting Using Local Data by Alfonso, Gerardo, Carnerero, A. Daniel, Ramirez, Daniel R., Alamo, Teodoro

“…Stock price forecasting is a relevant and challenging problem that has attracted a lot of interest from engineers and scientists. In this paper we apply two…”
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A simple rotor current estimation method for predictive control of multi‐phase drives by Satué, Manuel G., Arahal, Manuel R., Ortega, Manuel G., Ramírez, Daniel R.

“…Summary Predictive control of stator currents is a model‐based technique needing an estimation of rotor currents, which are normally not measured. These…”
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Neural Networks in Narrow Stock Markets by Alfonso, Gerardo, Ramirez, Daniel R.

“…Narrow markets are typically considered those that due to limited liquidity or peculiarities in its investor base, such as a particularly high concentration of…”
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Predictive Control of Multi-Phase Motor for Constant Torque Applications by Arahal, Manuel R., Barrero, Federico, Satué, Manuel G., Ramírez, Daniel R.

“…Constant torque motors are needed for rotary screw compressors that are used for cooling and other applications. In such systems, the torque demanded by the…”
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Receding horizon optimization of large trade orders by Alfonso, Gerardo, Daniel Carnerero, A., Ramirez, Daniel R., Alamo, Teodoro

“…The optimal execution of stock trades is a relevant and interesting problem as it is key in maximizing profits and reducing risks when investing in the stock…”
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Min-Max Predictive Control of a Five-Phase Induction Machine by Ramirez, Daniel R., Martin, Cristina, Kowal G., Agnieszka, Arahal, Manuel R.

“…In this paper, a fuzzy-logic based operator is used instead of a traditional cost function for the predictive stator current control of a five-phase induction…”
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From 3 fingers to 5 fingers dexterous hands by Ramírez Rebollo, Daniel R., Ponce, Pedro, Molina, Arturo

“…This document presents a resume of several robotic hands from 1983 to 2016, its aim is to cover this rapidly evolving field of robotics and provide relevant…”
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Nonlinear MPC for Tracking for a Class of Nonconvex Admissible Output Sets by Cotorruelo, Andres, Ramirez, Daniel R., Limon, Daniel, Garone, Emanuele

“…This article presents an extension to the nonlinear model predictive control (MPC) for tracking scheme able to guarantee convergence even in cases of nonconvex…”
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Probabilistically Certified Management of Data Centers Using Predictive Control by Carnerero, A. Daniel, Ramirez, Daniel R., Alamo, Teodoro, Limon, Daniel

“…Data centers are facilities with large number of servers providing cloud services. The increasing number of data centers in the last years has generated…”
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A Nonlinear Technical Indicator Selection Approach for Stock Markets. Application to the Chinese Stock Market by Alfonso, Gerardo, Ramirez, Daniel R.

“…In this paper we present a combinatorial nonlinear technical indicator approach for the identification of appropriate combinations of stock technical…”
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Kernel-Based State-Space Kriging for Predictive Control by Carnerero, A. Daniel, Ramirez, Daniel R., Limon, Daniel, Alamo, Teodoro

“…In this paper, we extend the state-space kriging (SSK) modeling technique presented in a previous work by the authors in order to consider non-autonomous…”
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Computation of maximal output admissible sets for linear systems with polynomial constraints by Cotorruelo, Andres, Garone, Emanuele, Kolmanovsky, Ilya V., Ramirez, Daniel R., Limon, Daniel

“…In this technical note we study the computation of the Maximal Output Admissible Set for linear systems subject to polynomial constraints. The computation of…”
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Randomized methods for design of uncertain systems: Sample complexity and sequential algorithms by Alamo, Teodoro, Tempo, Roberto, Luque, Amalia, Ramirez, Daniel R.

“…In this paper, we study randomized methods for feedback design of uncertain systems. The first contribution is to derive the sample complexity of various…”
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Kernel based State-Space Kriging: Application to predictive control by Carnerero, A. Daniel, Ramirez, Daniel R., Alamo, Teodoro

“…In this paper, we extend the State-Space Kriging (SSK) modelling technique presented in a previous work by the authors so that non autonomous systems can be…”
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Reference dependent invariant sets: Sum of squares based computation and applications in constrained control by Cotorruelo, Andres, Hosseinzadeh, Mehdi, Ramirez, Daniel R., Limon, Daniel, Garone, Emanuele

“…The goal of this paper is to present a systematic method to compute reference dependent positively invariant sets for systems subject to constraints. To this…”
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Control predictivo polifásico mediante dos constelaciones de vectores virtuales de tensión by Garrido Satué, Manuel, Ruiz Arahal, Manuel, Rodríguez Ramírez, Daniel, Barrero García, Federico

“…En el campo de los accionamientos eléctricos de velocidad variable ha aparecido recientemente el método predictivo basado en vectores virtuales de tensión…”
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Robust data-based predictive control of systems with parametric uncertainties: Paving the way for cooperative learning by Masero, Eva, Maestre, José M., Salvador, José R., Ramirez, Daniel R., Zhu, Quanyan

“…This article combines data and tube-based predictive control to deal with systems with bounded parametric uncertainty. This integration generates robustly…”
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State-Space Kriging: A Data-Driven Method to Forecast Nonlinear Dynamical Systems by Carnerero, A. Daniel, Ramirez, Daniel R., Alamo, Teodoro

“…This letter presents a new method for modeling dynamical systems. The method uses historical data of the outputs to predict the evolution of the system. The…”
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