Dynamical Systems

Complex systems are pervasive in many areas of science integrated in our daily lives. Examples include financial markets, highway transportation networks, telecommunication networks, world and country economies, social networks, immunological systems, living organisms, computational systems and electrical and mechanical structures. Complex systems are often composed of a large number of interconnected and interacting entities, exhibiting much richer global scale dynamics than the properties and behavior of individual entities. Complex systems are studied in many areas of natural sciences, social sciences, engineering and mathematical sciences. This special issue therefore intends to contribute towards the dissemination of the multifaceted concepts in accepted use by the scientific community. We hope readers enjoy this pertinent selection of papers which represents relevant examples of the state of the art in present day research. [...

On the outer synchronization of complex dynamical networks

Complex network models have become a major tool in the modeling and analysis of many physical, biological and social phenomena. A complex network exhibits behaviors which emerge as a consequence of interactions between its constituent elements, that is, remarkably, not the same as individual components. One particular topic that has attracted the researchers' attention is the analysis of how synchronization occurs in this class of models, with the expectation of gaining new insights of the interactions taking place in real-world complex systems. Most of the work in the literature so far has been focused on the synchronization of a collection of interconnected nodes (forming one single network), where each node is a dynamical system governed by a set of nonlinear differential equations, possibly displaying chaotic dynamics. In this thesis, we study an extended version of this problem. In particular, we consider a setup consisting of two complex networks which are coupled unidirectionally, in such a way that a set of signals from the master network are injected into the response network, and then investigate how synchronization is attained. Our analysis is fairly general. We impose few conditions on the network structure and do not assume that the nodes in a single network are synchronized. This work can be divided into two main parts; outer synchronization in fractional-order networks, and outer synchronization in ordinary networks. In both cases the system parameters are perturbed by bounded, time varying and unknown perturbations. The synchronizer feedback matrix is possibly perturbed with the same type of perturbations as well. In both cases, of fractional-order and ordinary networks, we build up several theorems that ensure the attainment of synchronization in various scenarios, including, e.g., cases in which the coupling matrix of the networks is non-diffusive (hence we can avoid this assumption, which is almost invariably made in the literature). In all the cases of interest, we show that the scheme for coupling the networks is very simple, as it reduces to the computation of a single gain matrix whose dimension is independent of the number of network nodes. The structure of the designed synchronizer is also very simple, making it convenient for real-world applications. Although all of the proposed schemes are assessed analytically, numerical results (obtained by computer simulations) are also provided to illustrate the proposed methods. ---------------------------------------Las redes complejas se han convertido en una herramienta fundamental en el análisis de muchos sistemas físicos, biológicos y sociales. Una red compleja presenta comportamientos que "emergen" como consecuencia de las interacciones entre sus elementos constituyentes pero que no se observan de forma individual en estos elementos. Un aspecto en concreto que ha atrapado la atención de muchos investigadores es el análisis de cómo se producen fenómenos de sincronización en esta clase de modelos, con la esperanza de alcanzar una mayor comprensión de las interacciones que tienen lugar en sistemas complejos del mundo real. La mayor parte del trabajo publicado hasta ahora ha estado centrado en la sincronización de una colección de nodos interconectados (que forman una única red con entidad propia), donde cada nodo es un sistema dinámico gobernado por un conjunto de ecuaciones diferenciales no lineales, posiblemente caóticas. En esta tesis estudiamos una versión extendida de este problema. En concreto, consideramos un sistema formado por dos redes complejas acopladas unidireccionalmente, de manera que un conjunto de señales de la red principal se inyectan en la red secundaria, e investigamos cómo se alcanza un estado de sincronización. Este fenómeno se conoce como "sincronización externa". Nuestro análisis es muy general. Se imponen pocas condiciones a las estructura de las redes y no es necesario suponer que los nodos de cada red estén sincronizados entre sí previamente. Esta memoria se puede dividir en dos bloques: la sincronización externa de redes descritas por ecuaciones diferenciales de orden fraccionario y la sincronización externa de redes ordinarias (descritas por ecuaciones diferenciales de orden entero). En ambos casos, se admite que los parámetros del sistema puedan estar sujetos a perturbaciones desconocidas, posiblemente variables con el tiempo, pero acotadas. La matriz de realimentación del esquema de sincronización puede sufrir el mismo tipo de perturbación. En ambos casos, con ecuaciones de orden fraccionario o entero, construimos varios teoremas que aseguran que se alcance la sincronización en escenarios diversos, incluyendo, por ejemplo, casos en los que la matriz de acoplamiento de las redes es no difusiva (por lo tanto, podemos evitar esta hipótesis, que es ubicua en la literatura). En todos los casos de interés, mostramos que el esquema necesario para interconectar las redes es muy simple, puesto que se reduce al cálculo de una única matriz de ganancia cuya dimensión es independiente de la dimensión total (número de nodos) de las redes. La estructura del sincronizados es también muy sencilla, lo que la hace potencialmente adecuada para aplicaciones del mundo real. Aunque todos los esquemas que se proponen se analizan de manera rigurosa, también se muestran resultados numéricos (obtenidos mediante simulación) para ilustrar los métodos propuestos.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Ángel María Bravo Santos.- Secretario: David Luengo García.- Vocal: Irene Sendiña Nada

Discrete Time Systems

Discrete-Time Systems comprehend an important and broad research field. The consolidation of digital-based computational means in the present, pushes a technological tool into the field with a tremendous impact in areas like Control, Signal Processing, Communications, System Modelling and related Applications. This book attempts to give a scope in the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications. We think that the contribution of the book enlarges the field of the Discrete-Time Systems with signification in the present state-of-the-art. Despite the vertiginous advance in the field, we also believe that the topics described here allow us also to look through some main tendencies in the next years in the research area

18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems: Proceedings

Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.:Welcome Address ........................ Page I Table of Contents ........................ Page III Symposium Committees .............. Page IV Special Thanks ............................. Page V Conference program (incl. page numbers of papers) ................... Page VI Conference papers Invited talks ................................ Page 1 Regular Papers ........................... Page 14 Wednesday, May 26th, 2010 ......... Page 15 Thursday, May 27th, 2010 .......... Page 110 Friday, May 28th, 2010 ............... Page 210 Author index ............................... Page XII

Raum-Zeit Interpolationstechniken

The photo-realistic modeling and animation of complex scenes in 3D requires a lot of work and skill of artists even with modern acquisition techniques. This is especially true if the rendering should additionally be performed in real-time. In this thesis we follow another direction in computer graphics to generate photo-realistic results based on recorded video sequences of one or multiple cameras. We propose several methods to handle scenes showing natural phenomena and also multi-view footage of general complex 3D scenes. In contrast to other approaches, we make use of relaxed geometric constraints and focus especially on image properties important to create perceptually plausible in-between images. The results are novel photo-realistic video sequences rendered in real-time allowing for interactive manipulation or to interactively explore novel view and time points.Das Modellieren und die Animation von 3D Szenen in fotorealistischer Qualität ist sehr arbeitsaufwändig, auch wenn moderne Verfahren benutzt werden. Wenn die Bilder in Echtzeit berechnet werden sollen ist diese Aufgabe um so schwieriger zu lösen. In dieser Dissertation verfolgen wir einen alternativen Ansatz der Computergrafik, um neue photorealistische Ergebnisse aus einer oder mehreren aufgenommenen Videosequenzen zu gewinnen. Es werden mehrere Methoden entwickelt die für natürlicher Phänomene und für generelle Szenen einsetzbar sind. Im Unterschied zu anderen Verfahren nutzen wir abgeschwächte geometrische Einschränkungen und berechnen eine genaue Lösung nur dort wo sie wichtig für die menschliche Wahrnehmung ist. Die Ergebnisse sind neue fotorealistische Videosequenzen, die in Echtzeit berechnet und interaktiv manipuliert, oder in denen neue Blick- und Zeitpunkte der Szenen frei erkundet werden können

Convergence of Intelligent Data Acquisition and Advanced Computing Systems

This book is a collection of published articles from the Sensors Special Issue on "Convergence of Intelligent Data Acquisition and Advanced Computing Systems". It includes extended versions of the conference contributions from the 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS’2019), Metz, France, as well as external contributions

Deterministic ethernet in a safety critical environment

This thesis explores the concept of creating safety critical networks with low congestion and latency (known as critical networking) for real time critical communication (safety critical environment). Critical networking refers to the dynamic management of all the application demands in a network within all available network bandwidth, in order to avoid congestion. Critical networking removes traffic congestion and delay to provide quicker response times. A Deterministic Ethernet communication system in a Safety Critical environment addresses the disorderly Ethernet traffic condition inherent in all Ethernet networks. Safety Critical environment means both time critical (delay sensitive) and content critical (error free). Ethernet networks however do not operate in a deterministic fashion, giving rise to congestion. To discover the common traffic patterns that cause congestion a detailed analysis was carried out using neural network techniques. This analysis has investigated the issues associated with delay and congestion and identified their root cause, namely unknown transmission conditions. The congestion delay, and its removal, was explored in a simulated control environment in a small star network using the Air-field communication standard. A Deterministic Ethernet was created and implemented using a Network Traffic Oscillator (NTO). NTO uses Critical Networking principles to transform random burst application transmission impulses into deterministic sinusoid transmissions. It is proved that the NTO has the potential to remove congestion and minimise latency. Based on its potential, it is concluded that the proposed Deterministic Ethernet can be used to improve network security as well as control long haul communication

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area

Computational Intelligence for Modeling, Control, Optimization, Forecasting and Diagnostics in Photovoltaic Applications

This book is a Special Issue Reprint edited by Prof. Massimo Vitelli and Dr. Luigi Costanzo. It contains original research articles covering, but not limited to, the following topics: maximum power point tracking techniques; forecasting techniques; sizing and optimization of PV components and systems; PV modeling; reconfiguration algorithms; fault diagnosis; mismatching detection; decision processes for grid operators

Learning Approaches to Analog and Mixed Signal Verification and Analysis

The increased integration and interaction of analog and digital components within a system has amplified the need for a fast, automated, combined analog, and digital verification methodology. There are many automated characterization, test, and verification methods used in practice for digital circuits, but analog and mixed signal circuits suffer from long simulation times brought on by transistor-level analysis. Due to the substantial amount of simulations required to properly characterize and verify an analog circuit, many undetected issues manifest themselves in the manufactured chips. Creating behavioral models, a circuit abstraction of analog components assists in reducing simulation time which allows for faster exploration of the design space. Traditionally, creating behavioral models for non-linear circuits is a manual process which relies heavily on design knowledge for proper parameter extraction and circuit abstraction. Manual modeling requires a high level of circuit knowledge and often fails to capture critical effects stemming from block interactions and second order device effects. For this reason, it is of interest to extract the models directly from the SPICE level descriptions so that these effects and interactions can be properly captured. As the devices are scaled, process variations have a more profound effect on the circuit behaviors and performances. Creating behavior models from the SPICE level descriptions, which include input parameters and a large process variation space, is a non-trivial task. In this dissertation, we focus on addressing various problems related to the design automation of analog and mixed signal circuits. Analog circuits are typically highly specialized and fined tuned to fit the desired specifications for any given system reducing the reusability of circuits from design to design. This hinders the advancement of automating various aspects of analog design, test, and layout. At the core of many automation techniques, simulations, or data collection are required. Unfortunately, for some complex analog circuits, a single simulation may take many days. This prohibits performing any type of behavior characterization or verification of the circuit. This leads us to the first fundamental problem with the automation of analog devices. How can we reduce the simulation cost while maintaining the robustness of transistor level simulations? As analog circuits can vary vastly from one design to the next and are hardly ever comprised of standard library based building blocks, the second fundamental question is how to create automated processes that are general enough to be applied to all or most circuit types? Finally, what circuit characteristics can we utilize to enhance the automation procedures? The objective of this dissertation is to explore these questions and provide suitable evidence that they can be answered. We begin by exploring machine learning techniques to model the design space using minimal simulation effort. Circuit partitioning is employed to reduce the complexity of the machine learning algorithms. Using the same partitioning algorithm we further explore the behavior characterization of analog circuits undergoing process variation. The circuit partitioning is general enough to be used by any CMOS based analog circuit. The ideas and learning gained from behavioral modeling during behavior characterization are used to improve the simulation through event propagation, input space search, complexity and information measurements. The reduction of the input space and behavioral modeling of low complexity, low information primitive elements reduces the simulation time of large analog and mixed signal circuits by 50-75%. The method is extended and applied to assist in analyzing analog circuit layout. All of the proposed methods are implemented on analog circuits ranging from small benchmark circuits to large, highly complex and specialized circuits. The proposed dependency based partitioning of large analog circuits in the time domain allows for fast identification of highly sensitive transistors as well as provides a natural division of circuit components. Modeling analog circuits in the time domain with this partitioning technique and SVM learning algorithms allows for very fast transient behavior predictions, three orders of magnitude faster than traditional simulators, while maintaining 95% accuracy. Analog verification can be explored through a reduction of simulation time by utilizing the partitions, information and complexity measures, and input space reduction. Behavioral models are created using supervised learning techniques for detected primitive elements. We will show the effectiveness of the method on four analog circuits where the simulation time is decreased by 55-75%. Utilizing the reduced simulation method, critical nodes can be found quickly and efficiently. The nodes found using this method match those found by an experienced layout engineer, but are detected automatically given the design and input specifications. The technique is further extended to find the tolerance of transistors to both process variation and power supply fluctuation. This information allows for corrections in layout overdesign or guidance in placing noise reducing components such as guard rings or decoupling capacitors. The proposed approaches significantly reduce the simulation time required to perform the tasks traditionally, maintain high accuracy, and can be automated