Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Jose R. Salvador"'
Publikováno v:
Journal of Process Control. 64:141-151
This paper presents a heuristic algorithm to implement a model predictive controller for systems with binary inputs in which the effect of the control signal on the response partially vanishes before reaching steady state, for example systems that ex
Publikováno v:
IFAC-PapersOnLine. 51:356-361
In this paper we propose a novel data-based predictive control scheme in which the prediction model is obtained from a linear combination of past system trajectories. The proposed controller optimizes the weights of this linear combination taking int
Publikováno v:
IFAC-PapersOnLine. 50:7187-7192
This paper presents a new algorithm for the predictive control of systems with on-off actuators that it is tailored for systems in which part of the state vector depends only slightly on past values of the control signal beyond a certain t — L time
Publikováno v:
IFAC-PapersOnLine. 50:6588-6593
A periodic nonlinear economic model predictive control (EMPC) with changing prediction horizon is proposed for the optimal management of water distribution networks (WDNs). The control model of the WDN is built by means of nonlinear differential-alge
Publikováno v:
ECC
This work presents a data driven control strategy able to track a set point without steady state error. The control sequence is computed as an affine combination of past control signals, which belong to a set of past closed loop trajectories stored i
Autor:
Enrico Terzi, Riccardo Scattolini, Jose R. Salvador, D. Muñoz de la Peña, Marcello Farina, Daniel R. Ramirez, Lorenzo Fagiano
Publikováno v:
CDC
A learning-based approach for robust predictive control design for multi-input multi-output (MIMO) linear systems is presented. The identification stage allows to obtain multi-step ahead prediction models and to derive tight uncertainty bounds. The i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0535a3b11f0d625c3fdd6484224b73c6
http://hdl.handle.net/11311/1141457
http://hdl.handle.net/11311/1141457
Publikováno v:
idUS. Depósito de Investigación de la Universidad de Sevilla
instname
instname
This work presents a data driven control strategy able to track a set point without steady-state error. The control sequence is computed as an affine combination of past control signals, which belong to a set of trajectories stored in a process histo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d28867638609f368ab97a584ac183cab
Publikováno v:
ECC
In this paper, a novel historian data based predictive control strategy is presented and used to control a water distribution network simulated using the EPANET software. The control actions are computed based on past historian data. The historian st
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
idUS. Depósito de Investigación de la Universidad de Sevilla
instname
Recercat. Dipósit de la Recerca de Catalunya
Digital.CSIC. Repositorio Institucional del CSIC
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
Universitat Politècnica de Catalunya (UPC)
idUS. Depósito de Investigación de la Universidad de Sevilla
instname
Recercat. Dipósit de la Recerca de Catalunya
Digital.CSIC. Repositorio Institucional del CSIC
idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
This paper addresses a novel economic model predictive control (MPC) formulation based on a periodicity constraint to achieve an optimal periodic operation for discrete-time linear systems. The proposed control strategy does not rely on forcing the t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e39f91d9519f2a8e7b49b3cd3287d296
Publikováno v:
Optimal Control - Applications & Methods; Mar2020, Vol. 41 Issue 2, p571-586, 16p