System identification and control of a 3D truss structure using PLID and LQG

This thesis deals with the experimental application of a system identification tech nique called pseudo-linear identification (PLID). PLID is a discrete-time, multi-input, multi-output (MEMO), state space, simultaneous parameter estimator and one step ahead state predictor of linear time invariant systems. No measurements are assumed perfect under PLED; that is the inputs and outputs are allowed to have zero mean white gaussian (ZMWG) additive noise. Furthermore, the states are also assumed to have additive ZMWG noise. Like most system identification techniques, PLED requires the system to be completely controllable and observable under the given actuator and sensor suite. The only firm assumption made on model structure is that the transfer function be strictly proper; that is, the frequency response is bounded and tends towards zero as frequency is in creased to infinity. Pole and zero locations are not confined; indeed, unstable systems can be identified, and furthermore, they can be controlled because PLED provides simultaneous one step ahead state predictions. Developed by Hopkins et. al. in 1988 [1], this method has seen little application (due in part to its youth); however, it is shown in the following pages to be a powerful technique for performing state space system identification, as well as on-line model order reduction. The experiment involves applying PLED to a 3 -Dimensional (3-D) kinematic truss structure (referred to here forward as the testbed ) in a batch mode (off-line). Batch mode identification, by definition, implies that the testbed does not change appreciably between the time it was identified and the time it will be controlled. For most kinematic structures, this is true. PLED can be used for real-time (on-line) system identification. However, due to the complexity of typical structures (e.g., flexible mechanical systems), and the high bandwidth of control (hundreds of hertz), this is not possible with current personal computer (PC) based controllers. Ultimately, the state space model generated by PLED will be used to design a closed loop controller for the testbed that will increase its damping twenty fold, from approximately 0.25% zeta to 5% zeta. Due to time constraints, we will only show simulation results of the closed loop system

Finite element and boundary element methods for contact with adhesion

[no abstract

Complete lattice projection autoassociative memories

Orientador: Marcos Eduardo Ribeiro do Valle MesquitaTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação CientíficaResumo: A capacidade do cérebro humano de armazenar e recordar informações por associação tem inspirado o desenvolvimento de modelos matemáticos referidos na literatura como memórias associativas. Em primeiro lugar, esta tese apresenta um conjunto de memórias autoassociativas (AMs) que pertecem à ampla classe das memórias morfológicas autoassociativas (AMMs). Especificamente, as memórias morfológicas autoassociativas de projeção max-plus e min-plus (max-plus e min-plus PAMMs), bem como suas composições, são introduzidas nesta tese. Tais modelos podem ser vistos como versões não distribuídas das AMMs propostas por Ritter e Sussner. Em suma, a max-plus PAMM produz a maior combinação max-plus das memórias fundamentais que é menor ou igual ao padrão de entrada. Dualmente, a min-plus PAMM projeta o padrão de entrada no conjunto de todas combinações min-plus. Em segundo, no contexto da teoria dos conjuntos fuzzy, esta tese propõe novas memórias autoassociativas fuzzy, referidas como classe das max-C e min-D FPAMMs. Uma FPAMM representa uma rede neural morfológica fuzzy com uma camada oculta de neurônios que é concebida para o armazenamento e recordação de conjuntos fuzzy ou vetores num hipercubo. Experimentos computacionais relacionados à classificação de padrões e reconhecimento de faces indicam possíveis aplicações dos novos modelos acima mencionadosAbstract: The human brain¿s ability to store and recall information by association has inspired the development various mathematical models referred to in the literature as associative memories. Firstly, this thesis presents a set of autoassociative memories (AMs) that belong to the broad class of autoassociative morphological memories (AMMs). Specifically, the max-plus and min-plus projection autoassociative morphological memories (max-plus and min-plus PAMMs), as well as their compositions, are introduced in this thesis. These models are non-distributed versions of the AMM models developed by Ritter and Sussner. Briefly, the max-plus PAMM yields the largest max-plus combination of the stored vectors which is less than or equal to the input pattern. Dually, the min-plus PAMM projects the input pattern into the set of all min-plus combinations. In second, in the context of fuzzy set theory, this thesis proposes new fuzzy autoassociative memories mentioned as class of the max-C and min-D FPAMMs. A FPAMM represents a fuzzy morphological neural network with a hidden layer of neurons that is designed for the storage and retrieval of fuzzy sets or vectors on a hypercube. Computational experiments concerning pattern classification and face recognition indicate possible applications of the aforementioned new AM modelsDoutoradoMatematica AplicadaDoutor em Matemática AplicadaCAPE

Numerical methods for space-time variational formulations of retarded potential boundary integral equations

[no abstract

Investigation of Wire Structures for Heat Transfer Enhancement in Compact Heat Exchangers

Verbesserte Wärmeübertrageroberflächen ermöglichen energieeffizientere, kompaktere und leichtere Wärmeübertrager. Eine spezifische Oberfläche, die in allen drei Kriterien optimal ist, gibt es nicht. Mit der Existenz dieses Zielkonflikts wurden und werden eine Vielzahl unterschiedlicher verbesserter Oberflächendesigns entwickelt. Innerhalb dieser Arbeit werden Wärmeübertrageroberflächen auf Basis zylindrischer Drähte/Stiftrippen mit Drahtdurchmessern in der Größenordnung von 100 μm für Flachrohranwendungen untersucht. Sehr hohe konvektive Wärmeübergangskoeffizienten und deutliche Materialeinsparungen können erwartet werden. Das Ziel dieser Arbeit ist es, das Potenzial dieser Drahtstrukturen abzuschätzen. Vier Schritte werden für die Abschätzung durchgeführt. Zunächst wird eine Methode zur Bewertung unterschiedlicher Oberflächenentwicklungen ausgearbeitet. Die Zielgrößen der Methode sind definiert als eine energetische, eine volumenspezifische und eine massenspezifische Effizienz. Im zweiten Schritt wird eine numerische Simulation der Fluidströmung durch verschiedene Drahtstrukturgeometrien durchgeführt und es werden Korrelationen für Kennzahlen der Thermo- und Fluiddynamik entwickelt. Im dritten Schritt wird die Machbarkeit der Herstellung von Drahtstruktur-Wärmeübertragern untersucht und eine Reihe von Wärmeübertragerproben wird experimentell im Hinblick auf ihre thermische und hydraulische Leistung geprüft. Im letzten Schritt werden die neu entwickelten Korrelationen verwendet, um die energetische, volumenspezifische und massenspezifische Effizienz der Drahtstrukturen unter geometrischen und operativen Randbedingungen zu optimieren. Die Begutachtung zeigt Vorteile der Drahtstrukturen auf für Anwendungen, bei denen Volumen- und insbesondere Masseneffizienz eine wesentliche Rolle spielen. Wird eine Kombination aus energie- und volumenbezogener Bewertung durchgeführt, sind die Drahtstrukturen bei kleinen und mittleren Luftgeschwindigkeiten unterhalb etwa 2.5 m/s vorteilhaft. Für höhere Geschwindigkeiten sind die untersuchten Drahtstrukturen nicht vorteilhaft im Vergleich zu üblichen Lamellen

Fuzzy Controllers

Trying to meet the requirements in the field, present book treats different fuzzy control architectures both in terms of the theoretical design and in terms of comparative validation studies in various applications, numerically simulated or experimentally developed. Through the subject matter and through the inter and multidisciplinary content, this book is addressed mainly to the researchers, doctoral students and students interested in developing new applications of intelligent control, but also to the people who want to become familiar with the control concepts based on fuzzy techniques. Bibliographic resources used to perform the work includes books and articles of present interest in the field, published in prestigious journals and publishing houses, and websites dedicated to various applications of fuzzy control. Its structure and the presented studies include the book in the category of those who make a direct connection between theoretical developments and practical applications, thereby constituting a real support for the specialists in artificial intelligence, modelling and control fields

Applications of Special Functions in High Order Finite Element Methods

In this thesis, we optimize different parts of high order finite element methods by application of special functions and symbolic computation. In high order finite element methods, orthogonal polynomials like the Jacobi polynomials are deeply rooted. A broad classical theory of these polynomials is known. Moreover, with modern computer algebra software we can extend this knowledge even further. Here, we apply this knowledge and software for different special functions to derive new recursive relations of local matrix entries. This massively optimizes the assembly time of local high order finite element matrices. Furthermore, the introduced algorithm is in optimal complexity. Moreover, we derive new high order dual functions, which result in fast interpolation operators. Lastly, efficient recursive algorithms for hanging node constraint matrices provided by this new dual functions are given