O desenvolvimento de métodos que permitam reproduzir numericamente o comportamento el de sistemas estruturais reais tem desa ado cientistas e pesquisadores a abordarem questões que vão além das condições de integridade do sistema. Neste sentido, uma série de novos parâmetros devem ser considerados durante um processo de otimização estrutural, zelando pela con abilidade em níveis aceitáveis enquanto que os custos esperados de falhas sejam minimizados. Aparentemente, os objetivos segurança e economia competem entre si, nesse contexto, a otimização do risco estrutural surge como uma formulação que permite equacionar este problema através do chamado custo esperado total. Nesta Tese, apresenta-se o desenvolvimento de uma técnica precisa para satisfazer os termos que compõem a função custo esperado total, isto é, uma técnica capaz de estimar a con abilidade de sistemas estruturais redundantes pela identi cação dos múltiplos modos de falha de uma maneira mais precisa que os métodos convencionais aproximados e de simulação. Além disso, análises inelásticas de estruturas de aço incluindo as não linearidades físicas e geométricas são consideradas utilizando o MCDG, além de leis constitutivas para prever o comportamento inelástico. Em posse destas informações, o algoritmo calcula o risco como sendo a probabilidade de falha multiplicada pela consequência econômica resultante desta falha. Ao risco são acrescentados os demais custos associados ao sistema estrutural, os quais não dependem dos parâmetros aleatórios do sistema e por isso denominados custos xos. Como produto, tem-se o custo esperado total, o qual corresponde a função objetivo do problema de otimização estrutural. Aplicações numéricas demonstram a precisão e e ciência da metodologia na avaliação da probabilidade de falha de problemas envolvendo funções de estado limite altamente não lineares com múltiplas regiões de falhas, assim como os efeitos causados pelas não linearidades físicas e geométricas nas análises probabil ísticas e na otimização do risco das estruturas. Os resultados demonstraram que, em relação às incertezas e consequências monetárias da falha, a estrutura ótima pode ser encontrada apenas pela formulação da otimização do risco, onde a con guração da estrutura e os limites de segurança são otimizados simultaneamente. A otimização do risco resulta numa estrutura ótima em termos mecânicos, custo esperado total e segurança. / The development of methods that allow to numerically reproduce the actual behavior of real structural systems has challenged scientists and researchers and urged them to address issues that extend beyond the integrity of a system. Therefore, a series of new parameters must be taken into account during the structural optimization process, looking for acceptable reliability levels while minimizing the expected failure costs. Apparently, safety and economy compete with each other, and in this context, structural risk optimization arises as a formulation that allows equating this problem through the so-called total expected cost. In this Thesis, an accurate technique is developed to satisfy the minimization of the total expected cost function i:e:; a technique that allows estimating the reliability of redundant structural systems by the identi cation of multiple failure modes in a more precise way than conventional approximation and simulation methods. Besides, inelastic analysis of steel trusses including both geometric and physical nonlinearities are considered using the generalized displacement control method, in addition to constitutive laws to predict the inelastic behavior. Based on this information, the algorithm calculates risk as the failure probability multiplied by the economic losses resulting from such failure. The other costs associated to the structual system are added to the actual risk and since they do not depend on system's random parameters, they are referred as xed costs. As result, one obtains the total expected cost, which corresponds to the objective function of the structural optimization problem. Numerical applications shows the accuracy and e ciency of the methodology in the evaluation of the failure probability of problems represented by high nonlinear limit state functions with multiple failure regions. It is also included the e ects of geometric and physical nonlinearities originated in the probabilistic analysis and risk optimization of truss structures. Results show that, in consideration of uncertainty and the monetary consequences of failure, the optimum structure can only be found by a risk optimization formulation, where structural con guration and safety margins are optimized simultaneously. Risk optimization yields a structure which is optimum in terms of mechanics and in terms of the compromise between cost and safety.

Made available in DSpace on 2014-12-17T14:56:04Z (GMT). No. of bitstreams: 1 AnfranseraiMD.pdf: 2426744 bytes, checksum: d0579aab855282deeac9bb5717c5ab5a (MD5) Previous issue date: 2002-08-02 / In conventional robot manipulator control, the desired path is specified in cartesian space and converted to joint space through inverse kinematics mapping. The joint references generated by this mapping are utilized for dynamic control in joint space. Thus, the end-effector position is, in fact, controlled indirectly, in open-loop, and the accuracy of grip position control directly depends on the accuracy of the available kinematic model. In this report, a new scheme for redundant manipulator kinematic control, based on visual servoing is proposed. In the proposed system, a robot image acquired through a CCD camera is processed in order to compute the position and orientation of each link of the robot arm. The robot task is specified as a temporal sequence of reference images of the robot arm. Thus, both the measured pose and the reference pose are specified in the same image space, and its difference is utilized to generate a cartesian space error for kinematic control purposes. The proposed control scheme was applied in a four degree-of-freedom planar redundant robot arm, experimental results are shown / No controle convencional de manipuladores rob?ticos, a trajet?ria desejada ? especificada em espa?o cartesiano e mapeada para espa?o de juntas atrav?s do modelo cinem?tico inverso do manipulador. As novas refer?ncias assim geradas s?o utilizadas para fins de controle din?mico em espa?o de juntas, desde modo a posi??o da garra ? controlada efetivamente em malha aberta e a precis?o do controle depende diretamente da precis?o do modelo cinem?tico dispon?vel. Esta disserta??o apresenta um novo algoritmo de controle cinem?tico para bra?os redundantes baseado em realimenta??o visual. No sistema proposto, a imagem do rob? ? captada por uma c?mera e processada, para obter a posi??o e orienta??o de cada um dos elos do rob?. A trajet?ria do rob? ? especificada na forma de uma seq??ncia temporal de imagens de refer?ncia do bra?o rob?tico. Assim, ambas as poses, a medida e a de refer?ncia s?o especificadas no mesmo espa?o de imagem e a sua diferen?a ? utilizada para gerar um erro em espa?o cartesiano para prop?sitos de controle cinem?tico. O esquema de controle proposto foi aplicado a um manipulador redundante planar de quatro graus de liberdade, resultados experimentais s?o apresentados

O desenvolvimento de métodos que permitam reproduzir numericamente o comportamento el de sistemas estruturais reais tem desa ado cientistas e pesquisadores a abordarem questões que vão além das condições de integridade do sistema. Neste sentido, uma série de novos parâmetros devem ser considerados durante um processo de otimização estrutural, zelando pela con abilidade em níveis aceitáveis enquanto que os custos esperados de falhas sejam minimizados. Aparentemente, os objetivos segurança e economia competem entre si, nesse contexto, a otimização do risco estrutural surge como uma formulação que permite equacionar este problema através do chamado custo esperado total. Nesta Tese, apresenta-se o desenvolvimento de uma técnica precisa para satisfazer os termos que compõem a função custo esperado total, isto é, uma técnica capaz de estimar a con abilidade de sistemas estruturais redundantes pela identi cação dos múltiplos modos de falha de uma maneira mais precisa que os métodos convencionais aproximados e de simulação. Além disso, análises inelásticas de estruturas de aço incluindo as não linearidades físicas e geométricas são consideradas utilizando o MCDG, além de leis constitutivas para prever o comportamento inelástico. Em posse destas informações, o algoritmo calcula o risco como sendo a probabilidade de falha multiplicada pela consequência econômica resultante desta falha. Ao risco são acrescentados os demais custos associados ao sistema estrutural, os quais não dependem dos parâmetros aleatórios do sistema e por isso denominados custos xos. Como produto, tem-se o custo esperado total, o qual corresponde a função objetivo do problema de otimização estrutural. Aplicações numéricas demonstram a precisão e e ciência da metodologia na avaliação da probabilidade de falha de problemas envolvendo funções de estado limite altamente não lineares com múltiplas regiões de falhas, assim como os efeitos causados pelas não linearidades físicas e geométricas nas análises probabil ísticas e na otimização do risco das estruturas. Os resultados demonstraram que, em relação às incertezas e consequências monetárias da falha, a estrutura ótima pode ser encontrada apenas pela formulação da otimização do risco, onde a con guração da estrutura e os limites de segurança são otimizados simultaneamente. A otimização do risco resulta numa estrutura ótima em termos mecânicos, custo esperado total e segurança. / The development of methods that allow to numerically reproduce the actual behavior of real structural systems has challenged scientists and researchers and urged them to address issues that extend beyond the integrity of a system. Therefore, a series of new parameters must be taken into account during the structural optimization process, looking for acceptable reliability levels while minimizing the expected failure costs. Apparently, safety and economy compete with each other, and in this context, structural risk optimization arises as a formulation that allows equating this problem through the so-called total expected cost. In this Thesis, an accurate technique is developed to satisfy the minimization of the total expected cost function i:e:; a technique that allows estimating the reliability of redundant structural systems by the identi cation of multiple failure modes in a more precise way than conventional approximation and simulation methods. Besides, inelastic analysis of steel trusses including both geometric and physical nonlinearities are considered using the generalized displacement control method, in addition to constitutive laws to predict the inelastic behavior. Based on this information, the algorithm calculates risk as the failure probability multiplied by the economic losses resulting from such failure. The other costs associated to the structual system are added to the actual risk and since they do not depend on system's random parameters, they are referred as xed costs. As result, one obtains the total expected cost, which corresponds to the objective function of the structural optimization problem. Numerical applications shows the accuracy and e ciency of the methodology in the evaluation of the failure probability of problems represented by high nonlinear limit state functions with multiple failure regions. It is also included the e ects of geometric and physical nonlinearities originated in the probabilistic analysis and risk optimization of truss structures. Results show that, in consideration of uncertainty and the monetary consequences of failure, the optimum structure can only be found by a risk optimization formulation, where structural con guration and safety margins are optimized simultaneously. Risk optimization yields a structure which is optimum in terms of mechanics and in terms of the compromise between cost and safety.

Moore’s law has until today mostly relied on shrinkage of the size of the devices inintegrated circuits. However, soon the granularity of the atoms will set a limit together with increased error probability of the devices. How can Moore’s law continue in thefuture? To overcome the increased error rate, we need to introduce redundancy. Applyingmethods from biology may be a way forward, using some of the strategies that transformsan egg into a fetus, but with electronic cells. A redundant system is less sensitive to failing components. We define electronic clayas a massive redundancy system of interchangeable and unified subsystems. We show how a mean voter, which is simpler than a majority voter, impact a redundant systemand how optimization can be formalized to minimize the impact of failing subsystems.The performance at given yield can be estimated with a first order model, without the need for Monte-Carlo simulations. The methods are applied and verified on a redundant finite-impulse response filter. The elementary circuit behavior of the memristor, ”the missing circuit element”, is investigated for fundamental understanding and how it can be used in applications. Different available simulation models are presented and the linear drift model is simulated with Joglekar-Wolf and Biolek window functions. Driven by a sinusoidal current, the memristor is a frequency dependent component with a cut-off frequency. The memristor can be densely packed and used in structures that both stores and compute in the same circuit, as neurons do. Surrounding circuit has to affect (write) and react (read) to the memristor with the same two terminals. We looked at artificial neural network for pattern recognition, but also for self organization in electronic cell array. Finally we look at wireless sensor network and how such system can adopt to the environment. This is also a massive redundant clay-like system. Future electronic systems will be massively redundant and adaptive. Moore’s law will continue, not based on shrinking device sizes, but on cheaper, numerous, unified and interchangeable subsystems.

Es ist vorhersehbar, dass die Luftmanipulatoren in den nächsten Jahrzehnten für viele Aufgaben eingesetzt werden, die entweder zu gefährlich oder zu teuer sind, um sie mit herkömmlichen Methoden zu bewältigen. In dieser Arbeit wird eine neuartige Lösung für die Gesamtsteuerung von hochredundanten Luftmanipulationssystemen vorgestellt. Die Ergebnisse werden auf eine Referenzkonfiguration angewendet, die als universelle Plattform für die Durchführung verschiedener Luftmanipulationsaufgaben etabliert wird. Diese Plattform besteht aus einer omnidirektionalen Drohne und einem seriellen Manipulator. Um den modularen Regelungsentwurf zu gewährleisten, werden zwei rechnerisch effiziente Algorithmen untersucht, um den virtuellen Eingang den Aktuatorbefehlen zuzuordnen. Durch die Integration eines auf einem künstlichen neuronalen Netz basierenden Diagnosemoduls und der rekonfigurierbaren Steuerungszuordnung in den Regelkreis, wird die Fehlertoleranz für die Drohne erzielt. Außerdem wird die Motorsättigung durch Rekonfiguration der Geschwindigkeits- und Beschleunigungsprofile behandelt. Für die Beobachtung der externen Kräfte und Drehmomente werden zwei Filter vorgestellt. Dies ist notwendig, um ein nachgiebiges Verhalten des Endeffektors durch die achsenselektive Impedanzregelung zu erreichen. Unter Ausnutzung der Redundanz des vorgestellten Luftmanipulators wird ein Regler entworfen, der nicht nur die Referenz der Endeffektor-Bewegung verfolgt, sondern auch priorisierte sekundäre Aufgaben ausführt. Die Wirksamkeit der vorgestellten Lösungen wird durch umfangreiche Tests überprüft, und das vorgestellte Steuerungssystem wird als sehr vielseitig und effektiv bewertet.:1 Introduction 2 Fundamentals 3 System Design and Modeling 4 Reconfigurable Control Allocation 5 Fault Diagnostics For Free Flight 6 Force and Torque Observer 7 Trajectory Generation 8 Hybrid Task Priority Control 9 System Integration and Performance Evaluation 10 Conclusion / In the following decades, aerial manipulators are expected to be deployed in scenarios that are either too dangerous for human beings or too expensive to be accomplished by traditional methods. This thesis presents a novel solution for the overall control of highly redundant aerial manipulation systems. The results are applied to a reference configuration established as a universal platform for performing various aerial manipulation tasks. The platform consists of an omnidirectional multirotor UAV and a serial manipulator. To ensure modular control design, two computationally efficient algorithms are studied to allocate the virtual input to actuator commands. Fault tolerance of the aerial vehicle is achieved by integrating a diagnostic module based on an artificial neural network and the reconfigurable control allocation into the control loop. Besides, the risk of input saturation of individual rotors is minimized by predicting and reconfiguring the speed and acceleration responses. Two filter-based observers are presented to provide the knowledge of external forces and torques, which is necessary to achieve compliant behavior of the end-effector through an axis-selective impedance control in the outer loop. Exploiting the redundancy of the proposed aerial manipulator, the author has designed a control law to achieve the desired end-effector motion and execute secondary tasks in order of priority. The effectiveness of the proposed designs is verified with extensive tests generated by following Monte Carlo method, and the presented control scheme is proved to be versatile and effective.:1 Introduction 2 Fundamentals 3 System Design and Modeling 4 Reconfigurable Control Allocation 5 Fault Diagnostics For Free Flight 6 Force and Torque Observer 7 Trajectory Generation 8 Hybrid Task Priority Control 9 System Integration and Performance Evaluation 10 Conclusion

In this dissertation, a fully scalable video coding system is proposed. This system achieves full temporal, resolution, and fidelity scalability by combining mesh-based motion-compensated temporal filtering, multihypothesis motion compensation, and an embedded 3D wavelet-coefficient coder. The first major contribution of this work is the introduction of the redundant-wavelet multihypothesis paradigm into motion-compensated temporal filtering, which is achieved by deploying temporal filtering in the domain of a spatially redundant wavelet transform. A regular triangle mesh is used to track motion between frames, and an affine transform between mesh triangles implements motion compensation within a lifting-based temporal transform. Experimental results reveal that the incorporation of redundant-wavelet multihypothesis into mesh-based motion-compensated temporal filtering significantly improves the rate-distortion performance of the scalable coder. The second major contribution is the introduction of a sliding-window implementation of motion-compensated temporal filtering such that video sequences of arbitrarily length may be temporally filtered using a finite-length frame buffer without suffering from severe degradation at buffer boundaries. Finally, as a third major contribution, a novel 3D coder is designed for the coding of the 3D volume of coefficients resulting from the redundant-wavelet based temporal filtering. This coder employs an explicit estimate of the probability of coefficient significance to drive a nonadaptive arithmetic coder, resulting in a simple software implementation. Additionally, the coder offers the possibility of a high degree of vectorization particularly well suited to the data-parallel capabilities of modern general-purpose processors or customized hardware. Results show that the proposed coder yields nearly the same rate-distortion performance as a more complicated coefficient coder considered to be state of the art.

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Speeding up addition is the key to faster digital signal processing (DSP). This can be achieved by exploiting the properties of redundant number systems. Their expanded symbol (digit) alphabet gives them multiple representations for most values. Utilising redundant representations at the output of an adder permits addition to be performed without carry-propagation, yielding fast, constant time performance irrespective of the word length. A resource efficient implementation of this fast adder structure is developed that re-purposes the fast carry logic of low-cost field programmable gate arrays (FPGAs). Experiments confirm constant time addition and show that it outperforms binary ripple carry addition at word lengths of greater than 44 bits in a Xilinx Spartan 3 FPGA and 24 bits in an Altera Cyclone III FPGA. Redundancy also provides other properties that can be exploited for performance gain. Some redundant representations will have more zero-symbols than others. These maximise the opportunities to exploit the multiplicative absorbing and additive identity properties of zero that when exercised reduce superfluous calculations. A serial recoding algorithm is developed that generates a redundant representation for a specified value with as few nonzero symbols as possible. Unlike previously published methods, it accepts a wide specification of number systems including those with irregularly spaced symbol alphabets. A Markov analysis and analysis of the elementary cycles in the formulated state machine provides average and worst case measures for the tested number system. Typically, the average number of non-zero symbols is less than a third and the worst case is less than a half. Further to the increase in zero-symbols, zero-dominance is proposed as a new property of redundant number representations. It promotes a set of representations that have uniquely positioned zero-symbols, in a Pareto-optimal sense. This set covers all representations of a value and is used to select representations to optimise the calculation of a dot-product. The dot-product or vector-multiply is a fundamental operation in DSP, since it is employed in filtering, correlation and convolution. The nonzero partial products can be packed together, substantially reducing the calculation time. The application of redundant number systems provides a two-fold benefit. Firstly, the number of nonzero partial products is reduced. Secondly, a novel opportunity is identified to use the representations in the zero-dominant set to optimise the packing further, gaining an extra 18% improvement. An implementation of the proposed dot-product with partial product packing is developed for a Cyclone II FPGA. It outperforms a quad-multiplier binary implementation in throughput by 50% . Redundant number systems excel at increasing performance in particular DSP subsystems, those that are numerically intensive and consist of considerable accumulation. The conversion back to a binary result is the performance bottleneck in the DSP algorithm, taking a time proportional to a binary adder. Therefore, redundant number systems are best utilised when this conversion cost can be amortised over many fast redundant additions, which is typical in many DSP and communications applications.

A formulation of impedance control for redundant manipulators is developed as a particular case of an optimal control problem. This formulation allows the planning and design of an impedance controller that benets from the stability and eficiency of an optimal controller. Moreover, to circumvent the high computational costs of computing an optimal controller, a sub-optimal feedback controller based on the state-dependent Ricatti equation (SDRE) approach is developed. This approach is then compared with the quadratic programming (QP) control formulation, commonly used to resolve redundancy of robotic manipulators. Numerical simulations of a redundant planar 4-DOF serial link manipulator show that the SDRE control formulation offers superior performance over the control strategy based QP, in terms of stability, performance and required control effort. / Uma formulação do controle de impedância para manipuladores redundantes é desenvolvida como um caso particular de um problema de controle ótimo. Essa formulação permite o planejamento e projeto de um controlador de impedância que se beneficia da estabilidade e eficiência de um controlador ótimo. Para evitar lidar com os elevados custos computacionais de se computar um controlador ótimo, um controlador em malha fechada sub-ótimo, baseado na abordagem das equações de Ricatti dependentes de estado (SDRE), é desenvolvido. Essa abordagem é comparada com a formulação de um controlador baseado em programação quadrática (QP), usualmente utilizado para resolver problemas de redundância em manipuladores robóticos. Simulações numéricas de um manipulador serial plano de quatro graus de liberdade mostram que o controlador baseado em SDRE oferece performance superior em relação a um controlador baseado em programação quadrática, em termos de estabilidade, performance e esforço de controle requerido do atuador.