An Efficient Maximization Algorithm With Implications in Min-Max Predictive Control

n this technical note, an algorithm for binary quadratic programs defined by matrices with band structure is proposed. It was shown in the article by T. Alamo, D. M. de la Pentildea, D. Limon, and E. F. Camacho, ldquoConstrained min-max predictive control: modifications of the objective function leading to polynomial complexity,rdquo IEEE Tran. Autom. Control , vol. 50, pp. 710-714, May 2005, that this class of problems arise in robust model predictive control when min-max techniques are applied. Although binary quadratic problems belongs to a class of NP-complete problems, the computational burden of the proposed maximization algorithm for band matrices is polynomial with the dimension of the optimization variable and exponential with the band size. Computational results and comparisons on several hundred test problems demonstrate the efficiency of the algorithm

Min–max MPC using a tractable QP problem

Min–max model predictive controllers (MMMPC) suffer from a great computational burden that is often circumvented by using approximate solutions or upper bounds of the worst possible case of a performance index. This paper proposes a computationally efficient MMMPC control strategy in which a close approximation of the solution of the min–max problem is computed using a quadratic programming problem. The overall computational burden is much lower than that of the min–max problem and the resulting control is shown to have a guaranteed stability. A simulation example is given in the paper

Min-Max MPC based on a computationally efficient upper bound of the worst case cost

Min-Max MPC (MMMPC) controllers [P.J. Campo, M. Morari, Robust model predictive control, in: Proc. American Control Conference, June 10–12, 1987, pp. 1021–1026] suffer from a great computational burden which limits their applicability in the industry. Sometimes upper bounds of the worst possible case of a performance index have been used to reduce the computational burden. This paper proposes a computationally efficient MMMPC control strategy in which the worst case cost is approximated by an upper bound based on a diagonalization scheme. The upper bound can be computed with O(n3) operations and using only simple matrix operations. This implies that the algorithm can be coded easily even in non-mathematical oriented programming languages such as those found in industrial embedded control hardware. A simulation example is given in the paper

Min-max model predictive control as a quadratic program

This paper deals with the implementation of min-max model predictive control for constrained linear systems with bounded additive uncertainties and quadratic cost functions. This type of controller has been shown to be a continuous piecewise affine function of the state vector by geometrical methods. However, no algorithm for computing the explicit solution has been given. In this paper, we show that the min-max optimization problem can be expressed as a multi-parametric quadratic program, and so, the explicit form of the controller may be determined by standard multi-parametric techniques

Necessidade de experimentação animal em Toxicologia

Se hace una reflexión sobre el nuevo Real Decreto 53/2013 por el que se establecen las normas básicas aplicables para la protección de los animales utilizados en experimentación y otros fines científicos, incluyendo la docencia; de acuerdo con la Ley 32/2007 solo se podrán utilizar animales cuando su uso esté justificado por la finalidad que se persigue, valorando su oportunidad siempre en términos de sus potenciales beneficios. Se establece como principio general la promoción e implantación del principio de las tres erres, el reemplazo, la reducción y el refinamiento de los procedimientos, en la evaluación toxicológica de nuevas sustancias, fomentando el de métodos alternativos a la experimentación con animales vivos, cuando ello lo permita. Por tanto vamos a considerar el desarrollo legislativo, la necesidad de la experimentación animal, los métodos alternativos y el proceso docente de la formación del personal que esté implicado. La conclusión definitiva es que la evaluación toxicológica por el momento no puede prescindir totalmente del uso de animales de experimentación.

La Toxicología en España y desarrollo de la Red Española de Métodos Alternativos a la Experimentación Animal REMA y de la Red Iberoamericana de Toxicología y Seguridad Química RITSQ

148 páginas con fotografías y tablas estadísticasConferencia invitada sobre La Toxicología en España y desarrollo de la Red Española de Métodos Alternativos a la Experimentación Animal REMA y de la Red Iberoamericana de Toxicología y Seguridad Química RITSQPeer reviewe

Programas y Carteles de Reuniones, Jornadas y Congresos de la AETOX desde 1971-2014

152 páginas con fotografías y tablas estadísticasHistoria de las Reuniones de la Sociedad Española de Toxicología desde 1971 a 2014Peer reviewe

Model predictive control techniques for hybrid systems

This paper describes the main issues encountered when applying model predictive control to hybrid processes. Hybrid model predictive control (HMPC) is a research field non-fully developed with many open challenges. The paper describes some of the techniques proposed by the research community to overcome the main problems encountered. Issues related to the stability and the solution of the optimization problem are also discussed. The paper ends by describing the results of a benchmark exercise in which several HMPC schemes were applied to a solar air conditioning plant.Ministerio de Eduación y Ciencia DPI2007-66718-C04-01Ministerio de Eduación y Ciencia DPI2008-0581

Método gradual teórico-práctico y colección de trozos selectos de los A.A. clásicos latinos y castellanos. libro primero, 1er curso

Precede al título: Traducción y composición latina

Relative Importance of Biotic and Abiotic Soil Components to Plant Growth and Insect Herbivore Population Dynamics

Background: Plants are affected by several aspects of the soil, which have the potential to exert cascading effects on the performance of herbivorous insects. The effects of biotic and abiotic soil characteristics have however mostly been investigated in isolation, leaving their relative importance largely unexplored. Such is the case for the dune grass Ammophila, whose decline under decreasing sand accretion is argued to be caused by either biotic or abiotic soil properties. Methodology/Principal Findings: By manipulating dune soils from three different regions, we decoupled the contributions of region, the abiotic and biotic soil component to the variation in characteristics of Ammophila arenaria seedlings and Schizaphis rufula aphid populations. Root mass fraction and total dry biomass of plants were affected by soil biota, although the latter effect was not consistent across regions. None of the measured plant properties were significantly affected by the abiotic soil component. Aphid population characteristics all differed between regions, irrespective of whether soil biota were present or absent. Hence these effects were due to differences in abiotic soil properties between regions. Although several chemical properties of the soil mixtures were measured, none of these were consistent with results for plant or aphid traits. Conclusions/Significance: Plants were affected more strongly by soil biota than by abiotic soil properties, whereas the opposite was true for aphids. Our results thus demonstrate that the relative importance of the abiotic and biotic component of soils can differ for plants and their herbivores. The fact that not all effects of soil properties could be detected across regions moreover emphasizes the need for spatial replication in order to make sound conclusions about the generality of aboveground-belowground interactions