534 resultados para cognitive control


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The Queensland University of Technology (QUT) allows the presentation of a thesis for the Degree of Doctor of Philosophy in the format of published or submitted papers, where such papers have been published, accepted or submitted during the period of candidature. This thesis is composed of seven published/submitted papers, of which one has been published, three accepted for publication and the other three are under review. This project is financially supported by an Australian Research Council (ARC) Discovery Grant with the aim of proposing strategies for the performance control of Distributed Generation (DG) system with digital estimation of power system signal parameters. Distributed Generation (DG) has been recently introduced as a new concept for the generation of power and the enhancement of conventionally produced electricity. Global warming issue calls for renewable energy resources in electricity production. Distributed generation based on solar energy (photovoltaic and solar thermal), wind, biomass, mini-hydro along with use of fuel cell and micro turbine will gain substantial momentum in the near future. Technically, DG can be a viable solution for the issue of the integration of renewable or non-conventional energy resources. Basically, DG sources can be connected to local power system through power electronic devices, i.e. inverters or ac-ac converters. The interconnection of DG systems to power system as a compensator or a power source with high quality performance is the main aim of this study. Source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, distortion at the point of common coupling in weak source cases, source current power factor, and synchronism of generated currents or voltages are the issues of concern. The interconnection of DG sources shall be carried out by using power electronics switching devices that inject high frequency components rather than the desired current. Also, noise and harmonic distortions can impact the performance of the control strategies. To be able to mitigate the negative effect of high frequency and harmonic as well as noise distortion to achieve satisfactory performance of DG systems, new methods of signal parameter estimation have been proposed in this thesis. These methods are based on processing the digital samples of power system signals. Thus, proposing advanced techniques for the digital estimation of signal parameters and methods for the generation of DG reference currents using the estimates provided is the targeted scope of this thesis. An introduction to this research – including a description of the research problem, the literature review and an account of the research progress linking the research papers – is presented in Chapter 1. One of the main parameters of a power system signal is its frequency. Phasor Measurement (PM) technique is one of the renowned and advanced techniques used for the estimation of power system frequency. Chapter 2 focuses on an in-depth analysis conducted on the PM technique to reveal its strengths and drawbacks. The analysis will be followed by a new technique proposed to enhance the speed of the PM technique while the input signal is free of even-order harmonics. The other techniques proposed in this thesis as the novel ones will be compared with the PM technique comprehensively studied in Chapter 2. An algorithm based on the concept of Kalman filtering is proposed in Chapter 3. The algorithm is intended to estimate signal parameters like amplitude, frequency and phase angle in the online mode. The Kalman filter is modified to operate on the output signal of a Finite Impulse Response (FIR) filter designed by a plain summation. The frequency estimation unit is independent from the Kalman filter and uses the samples refined by the FIR filter. The frequency estimated is given to the Kalman filter to be used in building the transition matrices. The initial settings for the modified Kalman filter are obtained through a trial and error exercise. Another algorithm again based on the concept of Kalman filtering is proposed in Chapter 4 for the estimation of signal parameters. The Kalman filter is also modified to operate on the output signal of the same FIR filter explained above. Nevertheless, the frequency estimation unit, unlike the one proposed in Chapter 3, is not segregated and it interacts with the Kalman filter. The frequency estimated is given to the Kalman filter and other parameters such as the amplitudes and phase angles estimated by the Kalman filter is taken to the frequency estimation unit. Chapter 5 proposes another algorithm based on the concept of Kalman filtering. This time, the state parameters are obtained through matrix arrangements where the noise level is reduced on the sample vector. The purified state vector is used to obtain a new measurement vector for a basic Kalman filter applied. The Kalman filter used has similar structure to a basic Kalman filter except the initial settings are computed through an extensive math-work with regards to the matrix arrangement utilized. Chapter 6 proposes another algorithm based on the concept of Kalman filtering similar to that of Chapter 3. However, this time the initial settings required for the better performance of the modified Kalman filter are calculated instead of being guessed by trial and error exercises. The simulations results for the parameters of signal estimated are enhanced due to the correct settings applied. Moreover, an enhanced Least Error Square (LES) technique is proposed to take on the estimation when a critical transient is detected in the input signal. In fact, some large, sudden changes in the parameters of the signal at these critical transients are not very well tracked by Kalman filtering. However, the proposed LES technique is found to be much faster in tracking these changes. Therefore, an appropriate combination of the LES and modified Kalman filtering is proposed in Chapter 6. Also, this time the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 7 proposes the other algorithm based on the concept of Kalman filtering similar to those of Chapter 3 and 6. However, this time an optimal digital filter is designed instead of the simple summation FIR filter. New initial settings for the modified Kalman filter are calculated based on the coefficients of the digital filter applied. Also, the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 8 uses the estimation algorithm proposed in Chapter 7 for the interconnection scheme of a DG to power network. Robust estimates of the signal amplitudes and phase angles obtained by the estimation approach are used in the reference generation of the compensation scheme. Several simulation tests provided in this chapter show that the proposed scheme can very well handle the source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, and synchronism of generated currents or voltages. The purposed compensation scheme also prevents distortion in voltage at the point of common coupling in weak source cases, balances the source currents, and makes the supply side power factor a desired value.

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The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, traditionally employ Bank-to-Turn maneuvers to change heading and thus direction of travel. Commonly overlooked is the effect these maneuvers have on downward facing body fixed sensors, which as a result of bank, point away from the feature during turns. By adopting Skid-to-Turn maneuvers, the aircraft is able change heading whilst maintaining wings level flight, thus allowing body fixed sensors to maintain a downward facing orientation. Eliminating roll also helps to improve data quality, as sensors are no longer subjected to the swinging motion induced as they pivot about an axis perpendicular to their line of sight. Traditional tracking controllers that apply an indirect approach of capturing ground based data by flying directly overhead can also see the feature off center due to steady state pitch and roll required to stay on course. An Image Based Visual Servo controller is developed to address this issue, allowing features to be directly tracked within the image plane. Performance of the proposed controller is tested against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to simulate the field of view of a body fixed camera.

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The potential of distributed reactive power control to improve the voltage profile of radial distribution feeders has been reported in literature by few authors. However, the multiple inverters injecting or absorbing reactive power across a distribution feeder may introduce control interactions and/or voltage instability. Such controller interactions can be alleviated if the inverters are allowed to operate on voltage droop. First, the paper demonstrates that a linear shallow droop line can maintain the steady state voltage profile close to reference, up to a certain level of loading. Then, impacts of the shallow droop line control on line losses and line power factors are examined. Finally, a piecewise linear droop line which can achieve reduced line losses and close to unity power factor at the feeder source is proposed.

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This paper describes modelling, estimation and control of the horizontal translational motion of an open-source and cost effective quadcopter — the MikroKopter. We determine the dynamics of its roll and pitch attitude controller, system latencies, and the units associated with the values exchanged with the vehicle over its serial port. Using this we create a horizontal-plane velocity estimator that uses data from the built-in inertial sensors and an onboard laser scanner, and implement translational control using a nested control loop architecture. We present experimental results for the model and estimator, as well as closed-loop positioning.

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In this paper we explore the ability of a recent model-based learning technique Receding Horizon Locally Weighted Regression (RH-LWR) useful for learning temporally dependent systems. In particular this paper investigates the application of RH-LWR to learn control of Multiple-input Multiple-output robot systems. RH-LWR is demonstrated through learning joint velocity and position control of a three Degree of Freedom (DoF) rigid body robot.

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Gray‘s (2000) revised Reinforcement Sensitivity Theory (r-RST) was used to investigate personality effects on information processing biases to gain-framed and loss-framed anti-speeding messages and the persuasiveness of these messages. The r-RST postulates that behaviour is regulated by two major motivational systems: reward system or punishment system. It was hypothesised that both message processing and persuasiveness would be dependent upon an individual‘s sensitivity to reward or punishment. Student drivers (N = 133) were randomly assigned to view one of four anti-speeding messages or no message (control group). Individual processing differences were then measured using a lexical decision task, prior to participants completing a personality and persuasion questionnaire. Results indicated that participants who were more sensitive to reward showed a marginally significant (p = .050) tendency to report higher intentions to comply with the social gain-framed message and demonstrate a cognitive processing bias towards this message, than those with lower reward sensitivity.

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Introduction / objectives Many strategies are used to control MRSA in hospitals. Only a few have been assessed in clinical trials and it is not obvious how findings should be generalised between settings. Uncertainty remains about which strategies represent the most appropriate use of scarce resources. We assess the cost-effectiveness of alternative MRSA screening and infection control strategies in England and Wales and discuss international relevance. Methods Models of MRSA transmission in ICUs and general medical (GM) wards were developed and used to evaluate different screening methods combined with decolonisation or isolation. Strategies were compared in terms of costs and health benefits (quality adjusted life years, QALYs). Different prevalences, proportions of high risk patients and ward sizes were investigated, and probabilistic sensitivity analyses (PSA) conducted. Results Decolonisation strategies were cost-saving in ICUs at a 5% admission prevalence, with admission and weekly PCR screening the most cost-effective (£3,929/QALY). In ICUs, screening and isolation reduced infection rates by ~10%. With admission prevalence ≤5%, targeting screening and isolation to high risk patients was optimal. In GM wards decolonisation and isolation strategies, though able to reduce MRSA infection rates up to ~50%, were not cost-effective. Conclusion The largest reductions in MRSA infection were achieved by screening and decolonisation strategies, and were cost-effective in ICU settings. In comparison, there is limited potential for screening and control strategies to be cost-effective in GM wards due to lower infection and mortality rates.

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Egon Brunswik proposed the concept of “representative design” for psychological experimentation, which has historically been overlooked or confused with another of Brunswik’s terms, ecological validity. In this article, we reiterate the distinc­tion between these two important concepts and highlight the relevance of the term representative design for sports psychology, practice, and experimental design. We draw links with ideas on learning design in the constraints-led approach to motor learning and nonlinear pedagogy. We propose the adoption of a new term, repre­sentative learning design, to help sport scientists, experimental psychologists, and pedagogues recognize the potential application of Brunswik’s original concepts, and to ensure functionality and action fidelity in training and learning environments.

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Objective: Older driver research has mostly focused on identifying that small proportion of older drivers who are unsafe. Little is known about how normal cognitive changes in aging affect driving in the wider population of adults who drive regularly. We evaluated the association of cognitive function and age, with driving errors. Method: A sample of 266 drivers aged 70 to 88 years were assessed on abilities that decline in normal aging (visual attention, processing speed, inhibition, reaction time, task switching) and the UFOV® which is a validated screening instrument for older drivers. Participants completed an on-road driving test. Generalized linear models were used to estimate the associations of cognitive factor with specific driving errors and number of errors in self-directed and instructor navigated conditions. Results: All errors types increased with chronological age. Reaction time was not associated with driving errors in multivariate analyses. A cognitive factor measuring Speeded Selective Attention and Switching was uniquely associated with the most errors types. The UFOV predicted blindspot errors and errors on dual carriageways. After adjusting for age, education and gender the cognitive factors explained 7% of variance in the total number of errors in the instructor navigated condition and 4% of variance in the self-navigated condition. Conclusion: We conclude that among older drivers errors increase with age and are associated with speeded selective attention particularly when that requires attending to the stimuli in the periphery of the visual field, task switching, errors inhibiting responses and visual discrimination. These abilities should be the target of cognitive training.

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Research on strategic decision making (SDM) has proliferated in the last decades. Most of the studies however, focus on the process and content of SDM, whereas relatively little interest was awarded to the factors associated with the decision maker influencing SDM. Moreover, most of the research on SDM focuses on large multinationals and little to no research is available that studies the ways in which entrepreneurs make strategic choices. The present study reviews the entrepreneurial traits that influence SDM. These traits are selected by analyzing the literature on the differences between entrepreneurs and managers, under the assumption that these factors are the most indicative for the particularities of entrepreneurial SDM. One of the most important theoretical propositions resulting from this analysis concerns the mediating role of cognitive complexity in the relation between these entrepreneurial traits and SDM outcomes. Directions for further research emerging from this conceptualization are identified and discussed.

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Train delay is one of the most important indexes to evaluate the service quality of the railway. Because of the interactions of movement among trains, a delayed train may conflict with trains scheduled on other lines at junction area. Train that loses conflict may be forced to stop or slow down because of restrictive signals, which consequently leads to the loss of run-time and probably enlarges more delays. This paper proposes a time-saving train control method to recover delays as soon as possible. In the proposed method, golden section search is adopted to identify the optimal train speed at the expected time of restrictive signal aspect upgrades, which enables the train to depart from the conflicting area as soon as possible. A heuristic method is then developed to attain the advisory train speed profile assisting drivers in train control. Simulation study indicates that the proposed method enables the train to recover delays as soon as possible in case of disturbances at railway junctions, in comparison with the traditional maximum traction strategy and the green wave strategy.

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Abstract: How has human information behavior evolved? Our paper explores this question in the form of notions, models and theories about the relationship between information behavior and human evolution. Alexander’s Ecological Dominance and Social Competition/Cooperation (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality. His model provides a basis for explaining the evolution of human socio-cognitive abilities, including ecological dominance, and social competition/cooperation. Our paper examines the human trait of information behavior as a socio-cognitive ability related to ecological dominance, and social competition/cooperation. The paper first outlines what is meant by information behavior from various interdisciplinary perspectives. We propose that information behavior is a socio-cognitive ability that is related to and enables other sociocognitive abilities such as human ecological dominance, and social competition/cooperation. The paper reviews the current state of evolutionary approaches to information behavior and future directions for this research . Keywords: information behavior, socio-cognitive ability, ecological dominance, social competition, social cooperation.