Catálogo de publicaciones - libros

A consequence of very fast technology development is the appearance of new phenomena in man made systems related to their large number of heterogeneous interacting components. Then because of resulting larger complexity over passing human operator capability, the system can no longer be only guided and controlled at trajectory level. A larger and more global delegation should be given the system at decision making, and it is proposed here to manage it at task level usually corresponding to well identified sequences in system operation. To succeed in this transfer attention has to be paid to the fact that there are in general many trajectories for one prescribed task. So a new and completely transparent link should be established between trajectory and task controls, both acting at their own levels in the system. The corresponding double loop control is developed here, and consists mainly in an asymptotically stable functional control acting at trajectory level as a whole, and explicit in terms of main system power bounds guaranteeing robustness inside a ball the size of which is the manifold generated by all system trajectories for task accomplishment. At higher level a new decision control based on trajectory utility for succeeding in the task is proposed, the role of which is to maintain system dynamics inside the selected trajectory manifold corresponding to task. With this two step control, human operator role is eased and can be more oriented toward higher coordination and maintenance management.

A simulation application may be modeled as a set of interacting entities within an environment. Such applications can be represented as a graph with a one-to-one mapping between vertices and entities and between edges and communications. As for classical applications, performances depend directly on a good load balancing of the entities between available computing devices and on the minimization of the impact of the communications between them. However, both objectives are contradictory and good performances may be achieved if and only if a good trade off is found. Our method for finding such a trade off leans on a bio-inspired method. We use competitive colonies of numerical ants, each one depositing colored pheromones, to find organizations of highly communicating entities.

The observation and modeling of natural Complex Systems (CSs) like the human nervous system, the evolution or the weather, allows the definition of special abilities and models reusable to solve other problems. For instance, Genetic Algorithms or Ant Colony Optimizations are inspired from natural CSs to solve optimization problems. This paper proposes the use of ant-based systems to solve various problems with a non assessing approach. This means that solutions to some problem are not evaluated. They appear as resultant structures from the activity of the system. Problems are modeled with graphs and such structures are observed directly on these graphs. Problems of Multiple Sequences Alignment and Natural Language Processing are addressed with this approach.

We describe here our perception of complex systems, of how we feel the different layers of description are an important part of a correct complex system simulation. We describe a rough models categorization between rules based and law based, of how these categories handled the levels of descriptions or scales. We then describe our fluid flow simulation, which combines different fineness of grain in a mixed approach of these categories. This simulation is built keeping in mind an ulterior use inside a more general aquatic ecosystem.

The structure of complexes made from DNA and suitable lipids (Lx), and designed for gene transfer was examined. Cryo Electron Microscopy, Small angle X-ray scattering and Dynamic Light Scattering showed that Lx form monodisperse and spherical multilamellar particles with a distinct concentric ring-like pattern. The same concentric and lamellar structure with different packing regimes was also observed when using linear dsDNA, ssDNA, oligodeoxynucleotides (ODN) and RNA. Lx ultrastructure is of highly ordered crystalline nature exhibiting lamellar and/or hexagonal phase. We have demonstrated structural similarities between this synthetic supramolecular auto-organization and that found in some viruses. Our data point towards the possible existence of a ubiquitous organization of genetic materials.

Comparing neuronal bursting models (NBM) with slow-fast autonomous dynamical systems (S-FADS), it appears that the specific features of a (NBM) do not allow a determination of the analytical slow manifold equation with the singular approximation method. So, a new approach based on Differential Geometry, generally used for (S-FADS), is proposed. Adapted to (NBM), this new method provides three equivalent manners of determination of the analytical slow manifold equation. Application is made for the three-variables model of neuronal bursting elaborated by Hindmarsh and Rose which is one of the most used mathematical representation of the widespread phenomenon of oscillatory burst discharges that occur in real neuronal cells.

Emergent properties are typically novel and unanticipated. In this paper, using chaos synchronization tools and ideas, we demonstrate, via two examples of three-dimensional autonomous differential systems, that, by simple uni- or bi-directional coupling, regular (resp. chaotic) behaviour can emerge from chaotic (resp. regular) behaviour.

In this work, a new delay dependent approach to deal with the robust filtering based synchronization problem for a class of structured uncertain neutral systems with unknown delays is proposed. The new approach gives the maximal size of the interval of evolution of the delay within which the filtering based synchronization process can be guaranteed. The obtained criterion can guarantee the filtering based synchronization process within any interval in , representing the evolution of the delay, where the size is less than the maximal size value obtained while solving the obtained criterion. Sufficient conditions to reduce the effect of the disturbance input on the filtering based synchronization error output to a prescribed level are established and expressed in terms of linear matrix inequalities. A numerical example is provided to illustrate the validity of the obtained results.

In this paper, we deal with some specific domains of applications to game theory. This is one of the major class of models in the new approaches of modelling in the economic domain. For that, we use genetic automata which allow to buid adaptive strategies for the players. We explain how the automata-based formalism proposed – matrix representation of automata with multiplicities – allows to define a semi-distance between the strategy behaviors. With that tools, we are able to generate an automatic processus to compute emergent systems of entities whose behaviors are represented by these genetic automata.

The purpose of the study consists in the development of a medical diagnosis system, capable of solving difficult medical diagnosis problems. In this paper we propose a novel medical diagnosis system. The medical diagnosis system is a heterogeneous system with human and artificial agents members specialized in medical diagnosis and assistant agents. The proposed diagnosis system can solve difficult medical diagnosis problems that cannot be solved by doctors or artificial systems specialized in medical diagnosis that operate in isolation. The problems solving by the diagnosis system is partially based on the blackboard-based problems solving.