Hybrid Reachability Analysis for Kuramoto-Lanchester Model

Cyber-physical systems are ubiquitous nowadays and play a significant role in people's daily life. These systems include, e.g., autonomous vehicles and aerospace systems. Since human lives rely on the performance of these systems, it is of utmost importance to ensure their reliability. However, their complexity makes analysis particularly challenging and computationally expensive. Thus, it is crucial to develop tools to efficiently analyze cyber-physical systems and their safety properties. Cyber-physical systems are often modeled by hybrid automata, i.e. finite-state machines augmented with ordinary differential equations. In the thesis, we investigate reachability analysis methods for hybrid automata. In particular, we extend JuliaReach, a framework for fast prototyping set-based reachability analysis algorithms, to support verification of hybrid automata. For this purpose, we add to JuliaReach concrete and lazy discrete post operators. Lazy operations are particularly efficient in flowpipe based reachability analysis with long sequences of computations. The implemented algorithms are interchangeable and support all three reachability scenarios available in JuliaReach for the purely continuous setting: techniques to analyze linear systems using support functions and zonotopes as well as Taylor model based analysis for nonlinear systems. In order to evaluate our methods, we apply them to the Kuramoto-Lanchester model. This model exhibits highly nonlinear dynamics and can be easily scaled, and thus is well-suited to assess performance of reachability analysis methods for hybrid automata

Fuzzy Systems

This book presents some recent specialized works of theoretical study in the domain of fuzzy systems. Over eight sections and fifteen chapters, the volume addresses fuzzy systems concepts and promotes them in practical applications in the following thematic areas: fuzzy mathematics, decision making, clustering, adaptive neural fuzzy inference systems, control systems, process monitoring, green infrastructure, and medicine. The studies published in the book develop new theoretical concepts that improve the properties and performances of fuzzy systems. This book is a useful resource for specialists, engineers, professors, and students

Journal of Telecommunications and Information Technology, 2017, nr 4

kwartalni

Particle Swarm Optimization

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field

An algorithmic approach to system architecting using shape grammar-cellular automata

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2008.Includes bibliographical references (p. 404-417).This thesis expands upon the understanding of the fundamentals of system architecting in order to more effectively apply this process to engineering systems. The universal concern about the system architecting process is that the needs and wants of the stakeholders are not being fully satisfied, primarily because too few design alternatives are created and ambiguity exists in the information required. At the same time, it is noted that nature offers a superb example of system architecting and therefore should be considered as a guide for the engineering of systems. Key features of nature's architecting processes include self-generation, diversity, emergence, least action (balance of kinetic and potential energy), system-of-systems organization, and selection for stability. Currently, no human-friendly method appears to exist that addresses the problems in the field of system architecture while at the same time emulating nature's processes. By adapting nature's self-generative approach, a systematic means is offered to more rigorously conduct system architecting and better satisfy stakeholders. After reviewing generative design methods, an algorithmic methodology is developed to generate a space of architectural solutions satisfying a given specification, local constraints, and physical laws. This approach combines a visually oriented human design interface (shape grammar) that provides an intuitive design language with a machine (cellular automata) to execute the system architecture's production set (algorithm). The manual output of the flexible shape grammar, the set of design rules, is transcribed into cellular automata neighborhoods as a sequenced production set that may include other simple programs (such as combinatoric instructions).(cont.) The resulting catalog of system architectures can be unmanageably large, so selection criteria (e.g., stability, matching interfaces, least action) are defined by the architect to narrow the solution space for stakeholder review. The shape grammar-cellular automata algorithmic approach was demonstrated across several domains of study. This methodology improves on the design's clarification and the number of design alternatives produced, which should result in greater stakeholder satisfaction. Of additional significance, this approach has shown value both in the study of the system architecting process, leading to the proposal of normative principles for system architecture, and in the modeling of systems for better understanding.by Thomas H. Speller, Jr.Ph.D

Recent Advances in Theoretical and Computational Modeling of Composite Materials and Structures

The advancement in manufacturing technology and scientific research has improved the development of enhanced composite materials with tailored properties depending on their design requirements in many engineering fields, as well as in thermal and energy management. Some representative examples of advanced materials in many smart applications and complex structures rely on laminated composites, functionally graded materials (FGMs), and carbon-based constituents, primarily carbon nanotubes (CNTs), and graphene sheets or nanoplatelets, because of their remarkable mechanical properties, electrical conductivity and high permeability. For such materials, experimental tests usually require a large economical effort because of the complex nature of each constituent, together with many environmental, geometrical and or mechanical uncertainties of non-conventional specimens. At the same time, the theoretical and/or computational approaches represent a valid alternative for designing complex manufacts with more flexibility. In such a context, the development of advanced theoretical and computational models for composite materials and structures is a subject of active research, as explored here for a large variety of structural members, involving the static, dynamic, buckling, and damage/fracturing problems at different scales

Hybrid programs

The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and PortoThis thesis studies hybrid systems, an emerging family of devices that combine in their models digital computations and physical processes. They are very quickly becoming a main concern in software engineering, which is explained by the need to develop software products that closely interact with physical attributes of their environment e. g. velocity, time, energy, temperature – typical examples range from micro-sensors and pacemakers, to autonomous vehicles, transport infrastructures and district-wide electric grids. But even if already widespread, these systems entail different combinations of programs with physical processes, and this renders their development a challenging task, still largely unmet by the current programming practices. Our goal is to address this challenge at its core; we wish to isolate the basic interactions between discrete computations and physical processes, and bring forth the programming paradigm that naturally underlies them. In order to do so in a precise and clean way, we resort to monad theory, a well established categorical framework for developing program semantics systematically. We prove the existence of a monad that naturally encodes the aforementioned interactions, and use it to develop and examine the foundations of the paradigm alluded above, which we call hybrid programming: we show how to build, in a methodical way, different programming languages that accommodate amplifiers, differential equations, and discrete assignments – the basic ingredients of hybrid systems – we list all program operations available in the paradigm, introduce if-then-else constructs, abort operations, and different types of feedback. Hybrid systems bring several important aspects of control theory into computer science. One of them is the notion of stability, which refers to a system’s capacity of avoiding significant changes in its output if small variations in its state or input occur. We introduce a notion of stability to hybrid programming, explore it, and show how to analyse hybrid programs with respect to it in a compositional manner. We also introduce hybrid programs with internal memory and show that they form the basis of a component-based software development discipline in hybrid programming. We develop their coalgebraic theory, namely languages, notions of behaviour, and bisimulation. In the process, we introduce new theoretical results on Coalgebra, including improvements of well-known results and proofs on the existence of suitable notions of behaviour for non-deterministic transition systems with infinite state spaces.Esta tese estuda sistemas híbridos, uma família emergente de dispositivos que envolvem diferentes interações entre computações digitais e processos físicos. Estes sistemas estão rapidamente a tornar-se elementos-chave da engenharia de software, o que é explicado pela necessidade de desenvolver produtos que interagem com os atributos físicos do seu ambiente e. g. velocidade, tempo, energia, e temperatura – exemplos típicos variam de micro-sensores e pacemakers, a veículos autónomos, infra-estruturas de transporte, e redes eléctricas distritais. Mas ainda que amplamente usados, estes sistemas são geralmente desenvolvidos de forma pouco sistemática nas prácticas de programação atuais. O objetivo deste trabalho é isolar as interações básicas entre computações digitais e processos físicos, e subsequentemente desenvolver o paradigma de programação subjacente. Para fazer isto de forma precisa, a nossa base de trabalho irá ser a teoria das mónadas, uma estrutura categórica para o desenvolvimento sistemático de semânticas na programação. A partir desta base, provamos a existência de uma mónada que capta as interações acima mencionadas, e usamo-la para desenvolver e examinar os fundamentos do paradigma de programação correspondente a que chamamos programação híbrida: mostramos como construir, de maneira metódica, diferentes linguagens de programação que acomodam amplificadores, equações diferenciais, e atribuições - os ingredientes básicos dos sistemas híbridos - caracterizamos todas as operações sobre programas disponíveis, introduzimos construções if-then-else, operações para lidar com excepções, e diferentes tipos de feedback. Os sistemas híbridos trazem vários aspectos da teoria de controlo para a ciência da computação. Um destes é a noção de estabilidade, que se refere à capacidade de um sistema de evitar mudanças drásticas no seu output se pequenas variações no seu estado ou input ocorrerem. Neste trabalho, desenvolvemos uma noção composicional de estabilidade para a programação híbrida. Introduzimos também programas híbridos com memória interna, que formam a base de uma disciplina de desenvolvimento de software baseado em componentes. Desenvolvemos a sua teoria coalgébrica, nomeadamente linguagens, noções de comportamento e bisimulação. Neste processo, introduzimos também novos resultados teóricos sobre Coalgebra, incluindo melhorias a resultados conhecidos e provas acerca da existência de noções de comportamento para sistemas de transição não determinísiticos com espaço de estados infinitos.The present work was financed by FCT – Fundação para a Ciência e a Tecnologia – with the grant SFRH/BD/52234/2013. Additional support was provided by the PTFLAD Chair on Smart Cities & Smart Governance and by project Dalí (POCI-01-0145-FEDER-016692), the latter funder by ERDF – European Regional Development Fund – through COMPETE 2020 – Operational Programme for Competitiveness and Internationalisation – together with FCT

Pattern Recognition

Pattern recognition is a very wide research field. It involves factors as diverse as sensors, feature extraction, pattern classification, decision fusion, applications and others. The signals processed are commonly one, two or three dimensional, the processing is done in real- time or takes hours and days, some systems look for one narrow object class, others search huge databases for entries with at least a small amount of similarity. No single person can claim expertise across the whole field, which develops rapidly, updates its paradigms and comprehends several philosophical approaches. This book reflects this diversity by presenting a selection of recent developments within the area of pattern recognition and related fields. It covers theoretical advances in classification and feature extraction as well as application-oriented works. Authors of these 25 works present and advocate recent achievements of their research related to the field of pattern recognition