873 resultados para EIL loop


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Increased awareness of environmental concerns has caused greater interest in developing power sources based on renewable technologies, such as wind. Due to the intermittent nature of the wind speed, output voltage and frequency of the direct driven permanent magnet synchronous generators (PMSG) are normally unsteady. Recently proposed Z-source inverter has been considered as a potential solution for grid interfacing wind power generators, thanks to buck-boost function that the single stage Z-source inverter can offer. Two control methodologies, namely unified controller for isolated operation and a multi-loop controller for grid interfaced operation are investigated in this paper. Theoretical analysis of these two control schemes is presented and experimental results to verify the effectiveness of the control method are also included.

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Describes the development and testing of a robotic system for charging blast holes in underground mining. The automation system supports four main tactical functions: detection of blast holes; teleoperated arm pose control; automatic arm pose control; and human-in-the-loop visual servoing. We present the system architecture, and analyse the major components, Hole detection is crucial for automating the process, and we discuss theoretical and practical aspects in detail. The sensors used are laser range finders and cameras installed in the end effector. For automatic insertion, we consider image processing techniques to support visual servoing the tool to the hole. We also discuss issues surrounding the control of heavy-duty mining manipulators, in particular, friction, stiction, and actuator saturation.

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This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.

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This thesis presents an approach for a vertical infrastructure inspection using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structure such as light and power distribution poles is a difficult task. There are challenges involved with developing such an inspection system, such as flying in close proximity to a target while maintaining a fixed stand-off distance from it. The contributions of this thesis fall into three main areas. Firstly, an approach to vehicle dynamic modeling is evaluated in simulation and experiments. Secondly, EKF-based state estimators are demonstrated, as well as estimator-free approaches such as image based visual servoing (IBVS) validated with motion capture ground truth data. Thirdly, an integrated pole inspection system comprising a VTOL platform with human-in-the-loop control, (shared autonomy) is demonstrated. These contributions are comprehensively explained through a series of published papers.

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"Future Perfect" is a solo artist exhibition featuring a 9 channel video installation, which is comprised of looped computer animation projections. In the first room, the big one, there are nine projections of looped computer animations. Many of these look like representations of gallery spaces containing sculptures, including rotating interpenetrating discs, bouncing coloured coffins, and jostling cardboard cubes (the cubes are blank, then covered in drawings, then covered in photographic imagery). In one video, a man and a woman walk towards one another but never get together. In the second room, an animated video on a flatscreen suggests an origin story. The subtitles tell how, in Russia, my great-grandfather made a joke about Stalin's child bride that cost him his life. That one isn’t a loop; it has a beginning, middle, and end. Lying on the floor, in front of the video, are two slightly crumpled mural prints of photographs of the ocean. There's also a clear Perspex cloud shape on a wall. Viewers will see themselves reflected in it, as if it were a distant hovering mirage. The first room of the exhibition, where objects are set in perpetual motion, is about departure. The second room registers some sense of arrival. The future perfect implies looking back on something that hasn't happened yet; future and past are conflated and the present is somehow deferred. The future perfect combines anticipation and reflection, and it relates to my interest in combining 3-D animation with other mediums like drawing, painting, and shot video. In my work, the virtual and actual coexist in tension, just like experience and expectation in the future perfect.

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Migraine is a common neurological disorder classified by the World Health Organisation (WHO) as one of the top twenty most debilitating diseases in the developed world. Current therapies are only effective for a proportion of sufferers and new therapeutic targets are desperately needed to alleviate this burden. Recently the role of epigenetics in the development of many complex diseases including migraine has become an emerging topic. By understanding the importance of acetylation, methylation and other epigenetic modifications, it then follows that this modification process is a potential target to manipulate epigenetic status with the goal of treating disease. Bisulphite sequencing and methylated DNA immunoprecipitation have been used to demonstrate the presence of methylated cytosines in the human D-loop of mitochondrial DNA (mtDNA), proving that the mitochondrial genome is methylated. For the first time, it has been shown that there is a difference in mtDNA epigenetic status between healthy controls and those with disease, especially for neurodegenerative and age related conditions. Given co-morbidities with migraine and the suggestive link between mitochondrial dysfunction and the lowered threshold for triggering a migraine attack, mitochondrial methylation may be a new avenue to pursue. Creative thinking and new approaches are needed to solve complex problems and a systems biology approach, where multiple layers of information are integrated is becoming more important in complex disease modelling.

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This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

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The main purpose of the rudder in ships is course keeping. However, the rudder can also be used, in some cases, to reject undesirable wave produced rolling motions. From a fundamental point of view, the main issues associated with this problem are the presence of a nonminimum phase zero and the single input two output nature of the system. In this paper, the limitations imposed on the achievable closed loop performance due to these issues are analyzed. This gives a deeper understanding of the problem and leads to conclusions regarding the inherent design trade-offs which hold regardless of the control strategy used.

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In traditional communication and information theory, noise is the demon Other, an unwelcome disruption in the passage of information. Noise is "anything that is added to the signal between its transmission and reception that is not intended by the source...anything that makes the intended signal harder to decode accurately". It is in Michel Serres' formulation, the "third man" in dialogue who is always assumed, and whom interlocutors continually struggle to exclude. Noise is simultaneously a condition and a by-product of the act of communication, it represents the ever present possibility of disruption, interruption, misunderstanding. In sonic or musical terms noise is cacophony, dissonance. For economists, noise is an arbitrary element, both a barrier to the pursuit of wealth and a basis for speculation. For Mick (Jeremy Sims) and his mate Kev (Ben Mendelsohn) in David Caesar's Idiot Box (1996), as for Hando (Russell Crowe) and his gang of skinheads in Geoffrey Wright's Romper Stomper (1992), or Dazey (Ben Mendelsohn) and Joe (Aden Young) in Wright's Metal Skin (1994) and all those like them starved of (useful) information and excluded from the circuit - the information poor - their only option, their only point of intervention in the loop, is to make noise, to disrupt, to discomfort, to become Serres' "third man", "the prosopopoeia of noise" (5).

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Wi-Fi is a commonly available source of localization information in urban environments but is challenging to integrate into conventional mapping architectures. Current state of the art probabilistic Wi-Fi SLAM algorithms are limited by spatial resolution and an inability to remove the accumulation of rotational error, inherent limitations of the Wi-Fi architecture. In this paper we leverage the low quality sensory requirements and coarse metric properties of RatSLAM to localize using Wi-Fi fingerprints. To further improve performance, we present a novel sensor fusion technique that integrates camera and Wi-Fi to improve localization specificity, and use compass sensor data to remove orientation drift. We evaluate the algorithms in diverse real world indoor and outdoor environments, including an office floor, university campus and a visually aliased circular building loop. The algorithms produce topologically correct maps that are superior to those produced using only a single sensor modality.

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Injection velocity has been recognized as a key variable in thermoplastic injection molding. Its closed-loop control is, however, difficult due to the complexity of the process dynamic characteristics. The basic requirements of the control system include tracking of a pre-determined injection velocity curve defined in a profile, load rejection and robustness. It is difficult for a conventional control scheme to meet all these requirements. Injection velocity dynamics are first analyzed in this paper. Then a novel double-controller scheme is adopted for the injection velocity control. This scheme allows an independent design of set-point tracking and load rejection and has good system robustness. The implementation of the double-controller scheme for injection velocity control is discussed. Special techniques such as profile transformation and shifting are also introduced to improve the velocity responses. The proposed velocity control has been experimentally demonstrated to be effective for a wide range of processing conditions.

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The water mouse, Xeromys myoides, is currently recognised as a vulnerable species in Australia, inhabiting a small number of distinct and isolated coastal regions of Queensland and the Northern Territory. An examination of the evolutionary history and contemporary influences shaping the genetic structure of this species is required to make informed conservation management decisions. Here, we report the first analysis undertaken on the phylogeography and population genetics of the water mouse across its mainland Australian distribution. Genetic diversity was assessed at two mitochondrial DNA (Cytochrome b, 1000 bp; D-loop, 400 bp) and eight microsatellite DNA loci. Very low genetic diversity was found, indicating that water mice underwent a recent expansion throughout their Australian range and constitute a single evolutionarily significant unit. Microsatellite analyses revealed that the highest genetic diversity was found in the Mackay region of central Queensland; population substructure was also identified, suggesting that local populations may be isolated in this region. Conversely, genetic diversity in the Coomera region of south-east Queensland was very low and the population in this region has experienced a significant genetic bottleneck. These results have significant implications for future management, particularly in terms of augmenting populations through translocations or reintroducing water mice in areas where they have gone extinct.

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Unidirectional inductive power transfer (UIPT) systems allow loads to consume power while bidirectional IPT (BIPT) systems are more suitable for loads requiring two way power flow such as vehicle to grid (V2G) applications with electric vehicles (EVs). Many attempts have been made to improve the performance of BIPT systems. In a typical BIPT system, the output power is control using the pickup converter phase shift angle (PSA) while the primary converter regulates the input current. This paper proposes an optimized phase shift modulation strategy to minimize the coil losses of a series – series (SS) compensated BIPT system. In addition, a comprehensive study on the impact of power converters on the overall efficiency of the system is also presented. A closed loop controller is proposed to optimize the overall efficiency of the BIPT system. Theoretical results are presented in comparison to both simulations and measurements of a 0.5 kW prototype to show the benefits of the proposed concept. Results convincingly demonstrate the applicability of the proposed system offering high efficiency over a wide range of output power.

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As the Internet becomes deeply embedded into consumers’ daily life, the digital virtual world brings significant influence to consumers’ self and narrative. Prior studies look at consumer self from either from a certain online space or comparing consumers’ physical and digital virtual selves but not the integration of the physical/digital world. This paper aims to explore the meanings of the digital virtual space on consumers’ narrative as a whole (their interests, dreams, or subjectivity). We utilise a postmodern concept of the cyborg to understand the cultural complexity, subjective meanings of, and the extent to which the digital virtual space plays a role in consumers’ self-narrative. We conducted in-depth interviews and gathered three consumer narratives. Our findings indicate that consumers’ narrative contains important fragments from both physical and digital virtual worlds and their physical and digital virtual selves form a feedback loop that strengthen their overall narrative.