5,420 research outputs found
Iterative nonlinear model predictive control of a PH reactor. A comparative analysis
IFAC WORLD CONGRESS (16) (16.2005.PRAGA, REPĂšBLICA CHECA)This paper describes the control of a batch pH reactor by a nonlinear predictive controller that improves performance by using data of past batches. The control strategy combines the feedback features of a nonlinear predictive controller with the learning capabilities of run-to-run control.
The inclusion of real-time data collected during the on-going batch run in addition to those from the past runs make the control strategy capable not only of eliminating repeated errors but also of responding to new disturbances that occur during the run. The paper uses these ideas to devise an integrated controller that increases the capabilities of Nonlinear Model Predictive Control (NMPC) with batch-wise learning. This controller tries to improve existing strategies by the use of a nonlinear controller devised along the last-run trajectory as well as by the inclusion of filters.
A comparison with a similar controller based upon a linear model is performed. Simulation results are presented in order to illustrate performance improvements that can be achieved by the new method over the conventional iterative controllers. Although the controller is designed for discrete-time systems, it can be applied to stable continuous plants after discretization
Iterative Nonlinear Control of a Semibatch Reactor. Stability Analysis
This paper presents the application of Iterative
Nonlinear Model Predictive Control, INMPC, to a semibatch
chemical reactor. The proposed control approach is derived
from a model-based predictive control formulation which takes
advantage of the repetitive nature of batch processes. The
proposed controller combines the good qualities of Model
Predictive Control (MPC) with the possibility of learning from
past batches, that is the base of Iterative Control. It uses a
nonlinear model and a quadratic objective function that is
optimized in order to obtain the control law. A stability proof
with unitary control horizon is given for nonlinear plants that
are affine in control and have linear output map.
The controller shows capabilities to learn the optimal trajectory after a few iterations, giving a better fit than a linear
non-iterative MPC controller. The controller has applications in
repetitive disturbance rejection, because they do not modify
the model for control purposes. In this application, some
experiments with a disturbance in inlet water temperature has
been performed, getting good results.Ministerio de Ciencia y TecnologĂa DPI2004-07444-C04-0
Application of iterative nonlinear model predictive control to a batch pilot reactor
IFAC WORLD CONGRESS (16) (16.2005.PRAGA, REPĂšBLICA CHECA)The aim of this article is to present the Iterative Model Predictive Controller, inmpc, as a good candidate to control chemical batch reactors. The proposed control approach is derived from a model-based predictive control formulation which takes advantage of the repetitive nature of batch processes. The proposed controller combines the good qualities of Model Predictive Control (mpc) with the possibility of learning from past batches, that is the base of Iterative Control. It uses a nonlinear model and a quadratic objective function that is optimized in order to obtain the control law. The controller is tested on a batch pilot reactor, and a comparison with an Iterative Learning Controller (ilc) is made. Under input constraints and for this nonlinear plant, a fast convergence rate is obtained with the proposed controller, showing good operational results. Although the controller is designed for discrete-time systems, it is a necessary condition that the continuous-time model does not present blow-up characteristics. The batch pilot reactor emulates an exothermal chemical reaction by means of electrical heating
Unemployment duration, unemployment benefits and recalls
We use administrative micro-data to investigate exits from unemployment of benefit recipients in Spain. Because the data allow us to distinguish between transitions to a new job and recall to the same employer, we apply a competing risks model with
observed and unobserved heterogeneity. We are also able to control for the type of
benefit received by the worker: insurance benefit or assistance benefit. We find
significant differences between the new job hazard and the recall hazard. Both hazard
rates increase around the time that insurance benefit elapses. We also find that when
larger firms recall unemployed workers they tend to do so faster than smaller firms. In
general, our results are consistent with predictions derived from search and implicit
contract models. They highlight the importance of taking into account the possibility of recall in the analysis of unemployment duration among unemployment benefit recipients
The Emergence of Native Podcasts in Journalism: Editorial Strategies and Business Opportunities in Latin America
This article analyses the state of the art of podcasting in the new digital landscape as well as the structures, editorial
strategies, and business models of native podcasts launched in Latin America over the last few years. To this end, a
multiple case study has been made to examine the way new digital outlets are using audio content. This qualitative research
is made up of a variety of approaches, such as interviews, online surveys of podcasters, as well as the collection
and analysis of secondary data. A specific aim of this comparative study was to include a sample of podcasts produced
by thirteen emerging media platforms from eight countries registered in the directory of digital natives conducted by
SembraMedia (https://www.sembramedia.org). This is a nonprofit organization dedicated to increasing the diversity and
quality of Spanish language content by helping digital media entrepreneurs become more sustainable and successful.
Results of this exploratory study reveal that native podcasting in Spanish is still expanding and that where the new media
are small in scale, they are more oriented to the full exploitation of the narrative and innovative possibilities of this
audio format and do not have responding to their target audiences’ needs as their main priority. These new media are
finding different ways to become monetised (mainly content production for clients, sponsored content, sponsorship, consulting
services, and advertising) and to make a profit
Exits from unemployment : recall or new job
This paper studies transitions out of unemployment in Spain distinguishing between recall to the same employer and reemployment in a new job. We use a large sample of newly unemployed workers obtained from Social Security records for Spain. These data contain information about each individual's employer identy before and after the unemployment spell. A discrete-time duration model with competing risks of exits serves us to investigate the factors that influence the probabilities of leaving unemployment to return to the same employer or to find a new job with a different employer. We find that the route to exit unemployment is determinant to understand the influence of individual an job characteristics on the hazard rate, as well as the latter dependence on unemployment duration. The recall hazard rate exhibits positive duration dependence during the first months and negative duration dependence thereafter (it is larger for females), while the new-job hazard presents positive duration dependence (it is larger for males
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