Javier Serrano

Min–max constrained quasi-infinite horizon model predictive control using linear programming

Abstract In this paper a quasi-infinite horizon 1-norm GPC is presented. This controller, combined with a global uncertainty description and an uncertainty band-updating procedure, has led to a robust algorithm with extremely low computational requirements. Only a linear programming (LP) problem needs to be solved to compute a control profile. This scheme can be successfully applied even to hard non-linear systems with relatively fast dynamics, as the large computational burden related to non-linear model predictive controllers is avoided. Simulation results performed on several constrained non-linear systems are provided.

NONLINEAR MPC VERSUS MPC USING ON-LINE LINEARISATION — A COMPARATIVE STUDY

Abstract One of the main drawbacks of NMPC schemes is the enormous computational effort these controllers require. On the other hand, linear MPC methods can be implemented solving just Quadratic Programming (QP) or Linear Programming (LP) problems. In this paper, an alternative implementation of NMPC suggested by De Keyser (1998) is implemented to reduce the computational effort. This methodology is based on on-line linearisation and solves and iterative procedure which, if convergent, provides with the solution of the NMPC problem. This controller is tested and compared with the purely nonlinear MPC schemes.

Fast single- and cross-show speaker diarization using binary key speaker modeling

Speaker diarization has become a key process within other speech processing systems which take advantage of single-speaker speech signals. Furthermore, finding recurrent speakers among a set of audio recordings, known as cross-show diarization, is gaining attention in the last years. Current state-of-the-art-systems provide good performance, but usually at the cost of long processing times. This limitation may make current systems not suitable for real-life applications. In this line, the speaker diarization approach based on binary key modeling provides a very fast yet accurate alternative. In this paper, we present the last improvements applied in binary key speaker diarization with the aim of further speeding up the process and improving performance. In addition, we propose a novel method for cross-show speaker diarization based on binary keys. Experimental results show the effectiveness of the proposed improvements for single-show speaker diarization, both in terms of speed and performance, obtaining a real-time factor of 0.0354xRT and a 16.8% relative improvement in performance. Furthermore, our proposed cross-show approach provides very competitive performance, just slightly worse than its single-show diarization counterpart, and exhibits a real time factor of 0.04xRT.

Global Speaker Clustering towards Optimal Stopping Criterion in Binary Key Speaker Diarization

The recently proposed speaker diarization technique based on binary keys provides a very fast alternative to state-of-the-art systems with little increase of Diarization Error Rate DER. Although the approach shows great potential, it also presents issues, mainly in the stopping criterion. Therefore, exploring alternative clustering/stopping criterion approaches is needed. Recently some works have addressed the speaker clustering as a global optimization problem in order to tackle the intrinsic issues of the Agglomerative Hierarchical Clustering AHC mainly the local-maximum-based decision making. This paper aims at adapting and applying this new framework to the binary key diarization system. In addition, an analysis of cluster purity across the AHC iterations is done using reference speaker ground-truth labels to select the purer clustering as input for the global framework. Experiments on the REPERE phase 1 test database show improvements of around 6% absolute DER compared to the baseline system output.

REAL TIME NON LINEAR CONSTRAINED MODEL PREDICTIVE CONTROL OF A GREENHOUSE

Abstract This paper describes the application of predictive control to the temperature regulation in agricultural processes. The main aim is to achieve climatic control of a greenhouse built in the Institute for Horticultural and Agricultural Engineering (ITG) of the University of Hannover (Germany). The MPC controller implemented here has the characteristic to take in account constraints in both manipulated and controlled variables using on-line linearisation, with very low computational burden. By means of a real time experiment, important advantages of the MPC algorithm are demonstrated, performance and mainly saving energy, using a soft optimal control effort. This controller has been compared with an adaptive P1D controller.

The e-Sentencias Prototype: A Procedural Ontology for Legal Multimedia Applications in the Spanish Civil Courts

Search, retrieval, and management of multimedia contents are challenging tasks for users and researchers alike. We introduce a software-hardware system for the global management of the multimedia contents produced by Spanish Civil Courts. The ultimate goal is to obtain an automatic classification of images and segments of the audiovisual records that, coupled with textual semantics, allows an efficient navigation and retrieval of judicial documents and additional legal sources. This paper describes our knowledge acquisition process, sets a typology of Spanish Civil hearings as performed in practice, and a preliminary procedural ontology at its actual stage of development (e-Sentencias ontology). A discussion on procedural, contextual and multimedia ontologies is also provided.

Improved binary key speaker diarization system

The recently proposed speaker diarization technique based on binary keys provides a very fast alternative to state-of-the-art systems. However, this speed up has the cost of a little increase in Diarization Error Rate (DER). This paper proposes a series of improvements to the original algorithm with the aim to get closer to state-of-the-art performance. First, several alternative similarity measures between binary key speaker/segment models are introduced. Second, we perform a first attempt at applying Intra-Session and IntraSpeaker Variability (ISISV) compensation within the binary diarization approach through the Nuisance Attribute Projection. Experimental results show the benefits of the newly introduced similarity metrics, as well as the potential of the Nuisance Attribute Projection for ISISV compensation in the binary key speaker diarization framework.

Hybrid Control of a Four Tanks System

Abstract Many processes, even being of a continuous nature, involve in its operation signals or rules different from the classical continuous variables represented by real variables and modelled by DAE. In practice they include on/off valves or other binary actuators, are subjected to logical operational rules, or are mixed with sequential operations. As a result, classical control does not fit very well with the overall operation of the plant. In this paper we consider the problem of hybrid control from a predictive control perspective, showing in a practical non trivial example with changing process structure, how the problem can be stated and solved.

Min-Max Constrained Quasi-Infinite Horizon Model Predictive Control Using Linear Programming

Abstract In this paper a quasi-infinite horizon 1-norm GPC is presented. This controller, combined with a global uncertainty description and an uncertainty bandupdating procedure, has led to a robust algorithm with extremely low computational requirements, since only an LP problem must be solved to compute a control move vector. This scheme can be successfully applied even to hard non-linear systems with fast dynamics, as the large computational burden related to non-linear model predictive controllers is avoided. Simulation results performed on several constrained non-linear systems are provided.

Persian-Spanish low-resource statistical machine translation through english as pivot language

This paper is an attempt to exclusively focus on investigating the pivot language technique in which a bridging language is utilized to increase the quality of the Persian-Spanish low-resource Statistical Machine Translation (SMT). In this case, English is used as the bridging language, and the Persian-English SMT is combined with the English-Spanish one, where the relatively large corpora of each may be used in support of the Persian-Spanish pairing. Our results indicate that the pivot language technique outperforms the direct SMT processes currently in use between Persian and Spanish. Furthermore, we investigate the sentence translation pivot strategy and the phrase translation in turn, and demonstrate that, in the context of the Persian-Spanish SMT system, the phrase-level pivoting outperforms the sentence-level pivoting. Finally we suggest a method called combination model in which the standard direct model and the best triangulation pivoting model are blended in order to reach a high-quality translation.