Nonlinear Time-Frequency Control Theory with Applications

Nonlinear control is an important subject drawing much attention. When a nonlinear system undergoes route-to-chaos, its response is naturally bounded in the time-domain while in the meantime becoming unstably broadband in the frequency-domain. Control scheme facilitated either in the time- or frequency-domain alone is insufficient in controlling route-to-chaos, where the corresponding response deteriorates in the time and frequency domains simultaneously. It is necessary to facilitate nonlinear control in both the time and frequency domains without obscuring or misinterpreting the true dynamics. The objective of the dissertation is to formulate a novel nonlinear control theory that addresses the fundamental characteristics inherent of all nonlinear systems undergoing route-to-chaos, one that requires no linearization or closed-form solution so that the genuine underlying features of the system being considered are preserved. The theory developed herein is able to identify the dynamic state of the system in real-time and restrain time-varying spectrum from becoming broadband. Applications of the theory are demonstrated using several engineering examples including the control of a non-stationary Duffing oscillator, a 1-DOF time-delayed milling model, a 2-DOF micro-milling system, unsynchronized chaotic circuits, and a friction-excited vibrating disk. Not subject to all the mathematical constraint conditions and assumptions upon which common nonlinear control theories are based and derived, the novel theory has its philosophical basis established in the simultaneous time-frequency control, on-line system identification, and feedforward adaptive control. It adopts multi-rate control, hence enabling control over nonstationary, nonlinear response with increasing bandwidth ? a physical condition oftentimes fails the contemporary control theories. The applicability of the theory to complex multi-input-multi-output (MIMO) systems without resorting to mathematical manipulation and extensive computation is demonstrated through the multi-variable control of a micro-milling system. The research is of a broad impact on the control of a wide range of nonlinear and chaotic systems. The implications of the nonlinear time-frequency control theory in cutting, micro-machining, communication security, and the mitigation of friction-induced vibrations are both significant and immediate

Functional Autonomy Techniques for Manipulation in Uncertain Environments

As robotic platforms are put to work in an ever more diverse array of environments, their ability to deploy visuomotor capabilities without supervision is complicated by the potential for unforeseen operating conditions. This is a particular challenge within the domain of manipulation, where significant geometric, semantic, and kinetic understanding across the space of possible manipulands is necessary to allow effective interaction. To facilitate adoption of robotic platforms in such environments, this work investigates the application of functional, or behavior level, autonomy to the task of manipulation in uncertain environments. Three functional autonomy techniques are presented to address subproblems within the domain. The task of reactive selection between a set of actions that incur a probabilistic cost to advance the same goal metric in the presence of an operator action preference is formulated as the Obedient Multi-Armed Bandit (OMAB) problem, under the purview of Reinforcement Learning. A policy for the problem is presented and evaluated against a novel performance metric, disappointment (analogous to prototypical MAB's regret), in comparison to adaptations of existing MAB policies. This is posed for both stationary and non-stationary cost distributions, within the context of two example planetary exploration applications of multi-modal mobility, and surface excavation. Second, a computational model that derives semantic meaning from the outcome of manipulation tasks is developed, which leverages physics simulation and clustering to learn symbolic failure modes. A deep network extracts visual signatures for each mode that may then guide failure recovery. The model is demonstrated through application to the archetypal manipulation task of placing objects into a container, as well as stacking of cuboids, and evaluated against both synthetic verification sets and real depth images. Third, an approach is presented for visual estimation of the minimum magnitude grasping wrench necessary to extract massive objects from an unstructured pile, subject to a given end effector's grasping limits, that is formulated for each object as a "wrench space stiction manifold". Properties are estimated from segmented RGBD point clouds, and a geometric adjacency graph used to infer incident wrenches upon each object, allowing candidate extraction object/force-vector pairs to be selected from the pile that are likely to be within the system's capability.</p

Nonlinear Time-Frequency Control Theory with Applications

Nonlinear control is an important subject drawing much attention. When a nonlinear system undergoes route-to-chaos, its response is naturally bounded in the time-domain while in the meantime becoming unstably broadband in the frequency-domain. Control scheme facilitated either in the time- or frequency-domain alone is insufficient in controlling route-to-chaos, where the corresponding response deteriorates in the time and frequency domains simultaneously. It is necessary to facilitate nonlinear control in both the time and frequency domains without obscuring or misinterpreting the true dynamics. The objective of the dissertation is to formulate a novel nonlinear control theory that addresses the fundamental characteristics inherent of all nonlinear systems undergoing route-to-chaos, one that requires no linearization or closed-form solution so that the genuine underlying features of the system being considered are preserved. The theory developed herein is able to identify the dynamic state of the system in real-time and restrain time-varying spectrum from becoming broadband. Applications of the theory are demonstrated using several engineering examples including the control of a non-stationary Duffing oscillator, a 1-DOF time-delayed milling model, a 2-DOF micro-milling system, unsynchronized chaotic circuits, and a friction-excited vibrating disk. Not subject to all the mathematical constraint conditions and assumptions upon which common nonlinear control theories are based and derived, the novel theory has its philosophical basis established in the simultaneous time-frequency control, on-line system identification, and feedforward adaptive control. It adopts multi-rate control, hence enabling control over nonstationary, nonlinear response with increasing bandwidth ? a physical condition oftentimes fails the contemporary control theories. The applicability of the theory to complex multi-input-multi-output (MIMO) systems without resorting to mathematical manipulation and extensive computation is demonstrated through the multi-variable control of a micro-milling system. The research is of a broad impact on the control of a wide range of nonlinear and chaotic systems. The implications of the nonlinear time-frequency control theory in cutting, micro-machining, communication security, and the mitigation of friction-induced vibrations are both significant and immediate

Surveillance Planning against Smart Insurgents in Complex Terrain

This study is concerned with finding a way to solve a surveillance system allocation problem based on the need to consider intelligent insurgency that takes place in a complex geographical environment. Although this effort can be generalized to other situations, it is particularly geared towards protecting military outposts in foreign lands. The technological assets that are assumed available include stare-devices, such as tower-cameras and aerostats, as well as manned and unmanned aerial systems. Since acquiring these assets depends on the ability to control and monitor them on the target terrain, their operations on the geo-location of interest ought to be evaluated. Such an assessment has to also consider the risks associated with the environmental advantages that are accessible to a smart adversary. Failure to consider these aspects might render the forces vulnerable to surprise attacks. The problem of this study is formulated as follows: given a complex terrain and a smart adversary, what types of surveillance systems, and how many entities of each kind, does a military outpost need to adequately monitor its surrounding environment? To answer this question, an analytical framework is developed and structured as a series of problems that are solved in a comprehensive and realistic fashion. This includes digitizing the terrain into a grid of cell objects, identifying high-risk spots, generating flight tours, and assigning the appropriate surveillance system to the right route or area. Optimization tools are employed to empower the framework in enforcing constraints--such as fuel/battery endurance, flying assets at adequate altitudes, and respecting the climbing/diving rate limits of the aerial vehicles--and optimizing certain mission objectives--e.g. revisiting critical regions in a timely manner, minimizing manning requirements, and maximizing sensor-captured image quality. The framework is embedded in a software application that supports a friendly user interface, which includes the visualization of maps, tours, and related statistics. The final product is expected to support designing surveillance plans for remote military outposts and making critical decisions in a more reliable manner

Analysis and design of composite panels with Stringer run-outs

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Fabricate

Bringing together pioneers in design and making within architecture, construction, engineering, manufacturing, materials technology and computation, Fabricate is a triennial international conference, now in its third year (ICD, University of Stuttgart, April 2017). Each year it produces a supporting publication, to date the only one of its kind specialising in Digital Fabrication. The 2017 edition features 32 illustrated articles on built projects and works in progress from academia and practice, including contributions from leading practices such as Foster + Partners, Zaha Hadid Architects, Arup, and Ron Arad, and from world-renowned institutions including ICD Stuttgart, Harvard, Yale, MIT, Princeton University, The Bartlett School of Architecture (UCL) and the Architectural Association

Aeronautical engineering: A continuing bibliography with indexes (supplement 214)

This bibliography lists 422 reports, articles and other documents introduced into the NASA scientific and technical information system in May, l987

Carbon Nano Tubes (CNTS) for the development of high-performance and smart composites.

Los nanotubos de carbono han atraído una enorme atención en los últimos años debido a sus propiedades multifuncionales sobresalientes. Un número cada vez mayor de trabajos de investigación de primera línea centran su interés en la búsqueda de aplicaciones prácticas que den uso de las notables propiedades de los nanotubos de carbono, incluyendo una elevada resistencia mecánica, propiedades piezorestivas, alta conductividad eléctrica, ligereza, excelente estabilidad química y térmica. En concreto, los estudios más recientes plantean dos grandes ramas de aplicación: fabricación de estructuras aligeradas de alta resistencia, y desarrollo de estructuras inteligentes. Con respecto a la primera línea de aplicación, el desarrollo de materiales compuestos ligeros de alta resistencia conecta con la creciente tendencia de la ingeniería estructural a incorporar materiales compuestos innovadores. Ejemplos recientes como el avión comercial Boeing 787, en el que la mitad del peso fue diseñado con materiales compuestos, predicen un futuro auspicioso para los nanotubos de carbono en la ingeniería aeronáutica. Sin embargo, aún resulta más interesante el comportamiento piezorresistivo de los compuestos reforzados con nanotubos de carbono, ya que posibilita la creación de estructuras que no sólo presentan altas capacidades portantes y reducido peso específico, sino que también ofrecen capacidades de auto-detección de deformaciones. Cuando el material se ve sometido a una deformación externa, en virtud de dicha propiedad piezoresistiva, la conductividad eléctrica varía de modo que es posible correlacionar su respuesta eléctrica con el campo deformacional aplicado. Estas propiedades multifuncionales entroncan con el nuevo paradigma de la Vigilancia de la Salud Estructural el cual aboga por el uso de materiales/estructuras inteligentes para resolver el problema de escalabilidad. En este contexto, la estructura o parte de ella presenta capacidades de auto-detección de tal manera que el mantenimiento basado en la condición puede llevarse a cabo sin necesidad de incluir sensores externos. En ambas líneas, la mayoría de las investigaciones han centrado el estudio en la experimentación, siendo mucho menor el número de trabajos que plantean modelos teóricos capaces de simular las propiedades mecánicas, eléctricas y electromecánicas de estos compuestos. Desde un punto de vista mecánico, existen estudios experimentales que informan acerca de los efectos perjudiciales sobre la respuesta macroscópica de aspectos micromecánicos tales como la tendencia a formar aglomerados, así como la curvatura de los nanotubos de carbono. Es por ello esencial desarrollar modelos teóricos que incorporen estos efectos y asistan al diseño de elementos estructurales reforzados con nanotubos de carbono. Respecto al estudio de las propiedades de conductividad y piezoresistividad, es esencial desarrollar formulaciones teóricas capaces de abordar la optimización de las propiedades de autodetección de deformaciones. Asimismo, es crucial comprender los diferentes mecanismos físicos que rigen la conductividad eléctrica de estos compuestos, de modo que sea posible incorporar su efecto diferencial dentro de un marco teórico. Por último, también es fundamental avanzar hacia el dominio del tiempo con el fin de desarrollar aplicaciones de vigilancia de la salud estructural basada en vibraciones. Con todo ello, los esfuerzos de esta tesis se han centrado en el modelado de las propiedades mecánicas, conductivas y electromecánicas de los compuestos reforzados con nanotubos de carbono para el desarrollo de estructuras inteligentes y de alta resistencia. Estas dos aplicaciones, a saber, compuestos de alta resistencia e inteligentes, han sido enmarcadas en el ámbito de los materiales poliméricos y de cemento, respectivamente. La razón de esta distinción se debe a la presunción de que los compuestos poliméricos pueden encontrar aplicaciones directas como paneles de fuselaje para estructuras de aeronaves, así como refuerzos mecánicos sobre estructuras pre-existentes. En cuanto al uso de nanotubos de carbono como inclusiones multifuncionales para compuestos inteligentes, tanto los materiales poliméricos como los de base cemento ofrecen una amplia gama de aplicaciones potenciales. Sin embargo, la similitud entre los compuestos de base cemento y el hormigón estructural convencional sugiere la idea de desarrollar sensores embebidos que ofrezcan una monitorización continua integrada sin comprometer a priori la durabilidad de la estructura huésped. Tanto las propiedades mecánicas como las conductivas han sido estudiadas mediante métodos de homogeneización de campo medio. Aspectos micromecánicos tales como la relación de aspecto, el contenido, la distribución de la orientación, la ondulación o la aglomeración de los nanotubos se han estudiado en detalle e incorporado al análisis de diferentes elementos estructurales. De manera similar, se han estudiado las propiedades de conductividad eléctrica y auto-detección de deformaciones bajo cargas cuasi-estáticas mediante modelos mixtos de homogenización micromecánica de Mori-Tanaka. Los principales mecanismos que gobiernan las propiedades de transporte eléctrico de estos compuestos, a saber, los efectos de túnel cuántico y la formación de canales conductores, se han incorporado por separado en las simulaciones a través de la teoría de percolación de fibras conductoras. Los resultados teóricos han sido validados con éxito mediante experimentos en condiciones de laboratorio. Finalmente, se ha desarrollado un nuevo circuito equivalente piezorresistivo/piezoeléctrico para el modelado electromecánico de materiales de base cemento reforzado con nanotubos de carbono en el dominio del tiempo. Con los experimentos como base de validación, se ha demostrado que el enfoque propuesto proporciona resultados precisos y ofrece un marco teórico apto para aplicaciones de procesamiento de señales y monitorización de la salud estructural. Se espera que el trabajo desarrollado en esta tesis pueda proporcionar herramientas valiosas que permitan profundizar en la comprensión de los principales aspectos físicos que controlan las propiedades mecánicas, eléctricas y electromecánicas de los compuestos reforzados con nanotubos de carbono. Además, se espera que los resultados presentados en esta tesis impulsen el desarrollo de materiales compuestos auto-sensibles embebidos para aplicaciones de vigilancia de la salud estructural.Carbon nanotubes have drawn enormous attention in recent years due to their outstanding multifunctional properties. A constantly growing number of works at the front line of research pursue potential applications of their remarkable physical properties, including elevated load-bearing capacity, piezoresistive properties, high electrical conductivity, lightness, and excellent chemical and thermal stability. In particular, most recent works contemplate two different application branches: manufacture of light-weight high-strength structures, and development of smart structures. With regard to the first line of application, the development of high-strength lightweight composites connects with the growing tendency of structural engineering to incorporate advanced composite materials. Recent noticeable examples such as the commercial aircraft Boeing 787, in which half of the total weight was designed with composite materials, predict an auspicious future for carbon nanotubes in aircraft structures. Nonetheless, what is even more interesting is the piezoresistive behavior of carbon nanotube-reinforced composites, which allows us to create structures that are not only high-strength and lightweight but also strain-sensitive. When the composites are subjected to external strain fields, in virtue of such piezoresistive properties, the overall electrical conductivity varies in such a way that it is possible to correlate the electrical response with the deformational state of the material. These multifunctional properties are in line with the new paradigm of Structural Health Monitoring which advocates the use of smart materials/structures to solve the scalability issue. In this context, the structure or part of it presents self-sensing capabilities in such a way that the condition-based maintenance can be conducted without necessitating external off-the-shelf sensors. In both lines, most investigations have focused on experimentation. Conversely, the number of theoretical models capable of simulating the mechanical, electrical, and electromechanical properties of these composites is still scarce. From a mechanical point of view, experiments have reported about the detrimental effects of micromechanical aspects such as agglomeration of fillers and curviness on the macroscopic properties. Hence, it is essential to develop theoretical models that allow us to include these effects and assist the design of composite structural elements. With regard to the study of the conductivity and piezoresistivity of carbon nanotube-reinforced composites, it is essential to develop theoretical formulations capable of tackling the optimization of their strain sensitivity. In addition, it is crucial to understand the different physical mechanisms that govern the electrical conductivity of these composites and include them separately in the theoretical framework. Finally, it is also fundamental to move towards the time domain in order to develop applications for vibration-based structural health monitoring. Overall, all the efforts of this thesis have been put into the modeling of the mechanical, conductive and electromechanical properties of carbon nanotube-reinforced composites for the development of high-strength and smart structures. These two applications, namely high-strength and smart composites, have been framed in the realm of polymeric and cement-based materials, respectively. The reason for this distinction is the idea that polymer composites with high load-bearing capacity can find direct applications as fuselage panels for aircraft structures, as well as mechanical reinforcements attached to pre-existing structures. With regard to the use of carbon nanotubes as fillers for smart composites, both polymer and cement-based materials offer an enormous range of potential applications. Nonetheless, the similarity between cement-based composites and regular structural concrete suggests the idea of developing continuous embedded monitoring systems without compromising the durability of the hosting structure a priori. Both mechanical and conductive properties have been studied by means of mean-field homogenization methods. Micromechanical aspects such as filler aspect ratio, content, orientation distribution, waviness or agglomeration have been studied in detail and incorporated to the analysis of different structural elements. Similarly, the electrical conductivity and strain-sensing properties of these composites under quasi-static loadings have been studied by means of mixed Mori-Tanaka micromechanics models. The main mechanisms that underlie the electrical conduction of these composites, namely quantum tunneling effects and conductive networks, have been distinguished by a percolative-type behavior. The theoretical results have been successfully validated by means of experiments under laboratory conditions. Finally, a novel piezoresistive/piezoelectric equivalent lumped circuit has been developed for the electromechanical modeling of carbon nanotube-reinforced cement-based materials in the time domain. With experiments as validating basis, the proposed approach has been shown to provide accurate results and offers a theoretical framework readily applicable to signal processing applications and structural health monitoring. The work developed in this thesis is envisaged to provide valuable tools to further the understanding of the main physical aspects that control the mechanical, electrical and electromechanical properties of composites doped with carbon nanotubes. Furthermore, it is expected to boost the development of embedded self-sensing carbon nanotube-reinforced composites for structural health monitoring applications.Premio Extraordinario de Doctorado U