954 resultados para uncertainties and disturbances


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In this paper, we consider the problem of designing state observers for a class of one-sided Lipschitz time-delay systems subject to disturbances. Not only the plants but also the outputs of the systems are subject to time delays and disturbances. The one-sided Lipschitz and quadraticallyinner-bounded conditions, which are more general than the traditional Lipschitz condition, are utilized to cover a broader class of nonlinearities. Based on the Lyapunov-Krasovskii approach, a robust observer design is proposed where synthesis condition is derived in terms of linear matrixinequality (LMI). A numerical example is given to show the effectiveness of the obtained results.

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Nesta dissertação é mostrada experimentalmente a existência de modos ressonantes em servomotores de corrente contínua sem núcleo de ferro. Até onde se sabe, não já publicações ou documentos técnicos de fabricantes que relatam esse efeito neste tipo de motor. Foi observado também que a frequência da ressonância é variável e que possivelmente depende da temperatura interna do motor. Conforme e mostrado em simulações técnicas tradicionais para o controle de motores podem não ser eficazes para lidar com esses modos ressonantes. Com o objetivo de amortecer a ressonância e obter o controle de velocidade e posição desses motores, são desenvolvidos controladores por modo deslizante baseados em funções de chaveamento obtidas por observadores de alto ganho. Esse controle e robusto a incertezas paramétricas e perturbações. Com o auxílio de simulações são mostrados os pontos fortes e limitações de cada um dos controladores.

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Neural networks (NNs) are an effective tool to model nonlinear systems. However, their forecasting performance significantly drops in the presence of process uncertainties and disturbances. NN-based prediction intervals (PIs) offer an alternative solution to appropriately quantify uncertainties and disturbances associated with point forecasts. In this paper, an NN ensemble procedure is proposed to construct quality PIs. A recently developed lower-upper bound estimation method is applied to develop NN-based PIs. Then, constructed PIs from the NN ensemble members are combined using a weighted averaging mechanism. Simulated annealing and a genetic algorithm are used to optimally adjust the weights for the aggregation mechanism. The proposed method is examined for three different case studies. Simulation results reveal that the proposed method improves the average PI quality of individual NNs by 22%, 18%, and 78% for the first, second, and third case studies, respectively. The simulation study also demonstrates that a 3%-4% improvement in the quality of PIs can be achieved using the proposed method compared to the simple averaging aggregation method.

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Prediction interval (PI) has been extensively used to predict the forecasts for nonlinear systems as PI-based forecast is superior over point-forecast to quantify the uncertainties and disturbances associated with the real processes. In addition, PIs bear more information than point-forecasts, such as forecast accuracy. The aim of this paper is to integrate the concept of informative PIs in the control applications to improve the tracking performance of the nonlinear controllers. In the present work, a PI-based controller (PIC) is proposed to control the nonlinear processes. Neural network (NN) inverse model is used as a controller in the proposed method. Firstly, a PI-based model is developed to construct PIs for every sample or time instance. The PIs are then fed to the NN inverse model along with other effective process inputs and outputs. The PI-based NN inverse model predicts the plant input to get the desired plant output. The performance of the proposed PIC controller is examined for a nonlinear process. Simulation results indicate that the tracking performance of the PIC is highly acceptable and better than the traditional NN inverse model-based controller.

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There are two main approaches for using in adaptive controllers. One is the so-called model reference adaptive control (MRAC), and the other is the so-called adaptive pole placement control (APPC). In MRAC, a reference model is chosen to generate the desired trajectory that the plant output has to follow, and it can require cancellation of the plant zeros. Due to its flexibility in choosing the controller design methodology (state feedback, compensator design, linear quadratic, etc.) and the adaptive law (least squares, gradient, etc.), the APPC is the most general type of adaptive control. Traditionally, it has been developed in an indirect approach and, as an advantage, it may be applied to non-minimum phase plants, because do not involve plant zero-pole cancellations. The integration to variable structure systems allows to aggregate fast transient and robustness to parametric uncertainties and disturbances, as well. In this work, a variable structure adaptive pole placement control (VS-APPC) is proposed. Therefore, new switching laws are proposed, instead of using the traditional integral adaptive laws. Additionally, simulation results for an unstable first order system and simulation and practical results for a three-phase induction motor are shown

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In this study, we proposed an adaptive fuzzy multi-surface sliding control (AFMSSC) for trajectory tracking of 6 degrees of freedom inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). It is shown that an adaptive fuzzy logic-based function approximator can be used to estimate the system uncertainties and an iterative multi-surface sliding control design can be carried out to control flight. Using AFMSSC on MIMO autonomous flight systems creates confluent control that can account for both matched and mismatched uncertainties, system disturbances and excitation in internal dynamics. It is proved that the AFMSSC system guarantees asymptotic output tracking and ultimate uniform boundedness of the tracking error. Simulation results are presented to validate the analysis.

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We address robust stabilization problem for networked control systems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Lyapunov functions, we derive the robustly stabilizing conditions for state feedback stabilization and design packet-loss dependent controllers by solving some matrix inequalities. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design method.

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Open pit mine operations are complex businesses that demand a constant assessment of risk. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal prices, metal grades, costs, schedules, quantities, and environmental issues, among others, which are not known with much certainty at the beginning of the project. Hence, mining projects present a considerable challenge to those involved in associated investment decisions, such as the owners of the mine and other stakeholders. In general terms, when an option exists to acquire a new or operating mining project, , the owners and stock holders of the mine project need to know the value of the mining project, which is the fundamental criterion for making final decisions about going ahead with the venture capital. However, obtaining the mine project’s value is not an easy task. The reason for this is that sophisticated valuation and mine optimisation techniques, which combine advanced theories in geostatistics, statistics, engineering, economics and finance, among others, need to be used by the mine analyst or mine planner in order to assess and quantify the existing uncertainty and, consequently, the risk involved in the project investment. Furthermore, current valuation and mine optimisation techniques do not complement each other. That is valuation techniques based on real options (RO) analysis assume an expected (constant) metal grade and ore tonnage during a specified period, while mine optimisation (MO) techniques assume expected (constant) metal prices and mining costs. These assumptions are not totally correct since both sources of uncertainty—that of the orebody (metal grade and reserves of mineral), and that about the future behaviour of metal prices and mining costs—are the ones that have great impact on the value of any mining project. Consequently, the key objective of this thesis is twofold. The first objective consists of analysing and understanding the main sources of uncertainty in an open pit mining project, such as the orebody (in situ metal grade), mining costs and metal price uncertainties, and their effect on the final project value. The second objective consists of breaking down the wall of isolation between economic valuation and mine optimisation techniques in order to generate a novel open pit mine evaluation framework called the ―Integrated Valuation / Optimisation Framework (IVOF)‖. One important characteristic of this new framework is that it incorporates the RO and MO valuation techniques into a single integrated process that quantifies and describes uncertainty and risk in a mine project evaluation process, giving a more realistic estimate of the project’s value. To achieve this, novel and advanced engineering and econometric methods are used to integrate financial and geological uncertainty into dynamic risk forecasting measures. The proposed mine valuation/optimisation technique is then applied to a real gold disseminated open pit mine deposit to estimate its value in the face of orebody, mining costs and metal price uncertainties.

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Visual adaptation regulates contrast sensitivity during dynamically changing light conditions (Crawford, 1947; Hecht, Haig & Chase, 1937). These adaptation dynamics are unknown under dim (mesopic) light levels when the rod (R) and long (L), medium (M) and short (S) wavelength cone photoreceptor classes contribute to vision via interactions in shared non-opponent Magnocellular (MC), chromatically opponent Parvocellular (PC) and Koniocellular (KC) visual pathways (Dacey, 2000). This study investigated the time-course of adaptation and post-receptoral pathways mediating receptor specific rod and cone interactions under mesopic illumination. A four-primary photostimulator (Pokorny, Smithson & Quinlan, 2004) was used to independently control the activity of the four photoreceptor classes and their post-receptoral visual athways in human observers. In the first experiment, the contrast sensitivity and time-course of visual adaptation under mesopic illumination were measured for receptoral (L, S, R) and post-receptoral (LMS, LMSR, L-M) stimuli. An incremental (Rapid-ON) sawtooth conditioning pulse biased detection to ON-cells within the visual pathways and sensitivity was assayed relative to pulse onset using a briefly presented incremental probe that did not alter adaptation. Cone.Cone interactions with luminance stimuli (L cone, LMS, LMSR) reduced sensitivity by 15% and the time course of recovery was 25± 5ms-1 (μ ± SEM). PC mediated (+L-M) chromatic stimuli sensitivity loss was less (8%) than for luminance and recovery was slower (μ = 2.95 ± 0.05 ms-1), with KC mediated (S cone) chromatic stimuli showing a high sensitivity loss (38%) and the slowest recovery time (1.6 ± 0.2 ms-1). Rod-Rod interactions increased sensitivity by 20% and the time course of recovery was 0.7 ± 0.2 ms-1 (μ ± SD). Compared to these interaction types, Rod-Cone interactions reduced sensitivity to a lesser degree (5%) and showed the fastest recovery (μ = 43 ± 7 ms-1). In the second experiment, rod contribution to the magnocellular, parvocellular and koniocellular post-receptoral pathways under mesopic illumination was determined as a function of incremental stimulus duration and waveform (rectangular; sawtooth) using a rod colour match procedure (Cao, Pokorny & Smith, 2005; Cao, Pokorny, Smith & Zele, 2008a). For a 30% rod increment, a cone match required a decrease in [L/(L+M)] and an increase in [L+M] and [S/(L+M)], giving a greenish-blue and brighter appearance for probe durations of 75 ms or longer. Probe durations less than 75 ms showed an increase in [L+M] and no change in chromaticity [L/(L+M) or S/(L+M)], uggesting mediation by the MC pathway only for short duration rod stimuli. s We advance previous studies by determining the time-course and nature of photoreceptor specific retinal interactions in the three post-receptoral pathways under mesopic illumination. In the first experiment, the time-course of adaptation for ON cell processing was determined, revealing opponent cell facilitation in chromatic PC and KC pathways. The Rod-Rod and Rod-Cone data identify previously unknown interaction types that act to maintain contrast sensitivity during dynamically changing light conditions and improve the speed of light adaptation under mesopic light levels. The second experiment determined the degree of rod contribution to the inferred post-eceptoral pathways as a function of the temporal properties of the rod signal. r The understanding of the mechanisms underlying interactions between photoreceptors under mesopic illumination has implications for the study of retinal disease. Visual function has been shown to be reduced in persons with age-related maculopathy (ARM) risk genotypes prior to clinical signs of the disease (Feigl, Cao, Morris & Zele, 2011) and disturbances in rod-mediated adaptation have been shown in early phases of ARM (Dimitrov, Guymer, Zele, Anderson & Vingrys, 2008; Feigl, Brown, Lovie-Kitchin & Swann, 2005). Also, the understanding of retinal networks controlling vision enables the development of international lighting standards to optimise visual performance nder dim light levels (e.g. work-place environments, transportation).

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How do agents with limited cognitive capacities flourish in informationally impoverished or unexpected circumstances? Aristotle argued that human flourishing emerged from knowing about the world and our place within it. If he is right, then the virtuous processes that produce knowledge, best explain flourishing. Influenced by Aristotle, virtue epistemology defends an analysis of knowledge where beliefs are evaluated for their truth and the intellectual virtue or competences relied on in their creation. However, human flourishing may emerge from how degrees of ignorance are managed in an uncertain world. Perhaps decision-making in the shadow of knowledge best explains human wellbeing—a Bayesian approach? In this dissertation I argue that a hybrid of virtue and Bayesian epistemologies explains human flourishing—what I term homeostatic epistemology. Homeostatic epistemology supposes that an agent has a rational credence p when p is the product of reliable processes aligned with the norms of probability theory; whereas an agent knows that p when a rational credence p is the product of reliable processes such that: 1) p meets some relevant threshold for belief (such that the agent acts as though p were true and indeed p is true), 2) p coheres with a satisficing set of relevant beliefs and, 3) the relevant set of beliefs is coordinated appropriately to meet the integrated aims of the agent. Homeostatic epistemology recognizes that justificatory relationships between beliefs are constantly changing to combat uncertainties and to take advantage of predictable circumstances. Contrary to holism, justification is built up and broken down across limited sets like the anabolic and catabolic processes that maintain homeostasis in the cells, organs and systems of the body. It is the coordination of choristic sets of reliably produced beliefs that create the greatest flourishing given the limitations inherent in the situated agent.

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Virtual working environments are intrinsic to the contemporary workplace and collaborative skills are a vital graduate capability. To develop students’ collaborative skills, first year medical laboratory science students undertake a group poster project, based on a blended learning model. Learning is scaffolded in lectures, workshops in collaborative learning spaces, practitioner mentoring sessions, and online resources. Google Drive provides an online collaborative space for students to realise tangible outcomes from this learning. A Google Drive document is created for each group and shared with members. In this space, students assign tasks and plan workflow, share research, progressively develop poster content, reflect and comment on peer contributions and use the messaging functions to ‘talk’ to group members. This provides a readily accessible, transparent record of group work, crucial in peer assessment, and a communication channel for group members and the lecturer, who can support groups if required. This knowledge creation space also augments productivity and effectiveness of face-to-face collaboration. As members are randomly allocated to groups and are often of diverse backgrounds and unknown to each other, resilience is built as students navigate the uncertainties and complexities of group dynamics, learning to focus on the goal of the team task as they constructively and professionally engage in team dialogue. Students are responsible and accountable for individual and group work. The use of Google Drive was evaluated in a survey including Likert scale and open ended qualitative questions. Statistical analysis was carried out. Results show students (79%) valued the inclusion of online space in collaborative work and highly appreciated (78%) the flexibility provided by Google Drive, while recognising the need for improved notification functionality. Teaching staff recognised the advantages in monitoring and moderating collaborative group work, and the transformational progression in student collaborative as well as technological skill acquisition, including professional dialogue.

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Educating responsive graduates. Graduate competencies include reliability, communication skills and ability to work in teams. Students using Collaborative technologies adapt to a new working environment, working in teams and using collaborative technologies for learning. Collaborative Technologies were used not simply for delivery of learning but innovatively to supplement and enrich research-based learning, providing a space for active engagement and interaction with resources and team. This promotes the development of responsive ‘intellectual producers’, able to effectively communicate, collaborate and negotiate in complex work environments. Exploiting technologies. Students use ‘new’ technologies to work collaboratively, allowing them to experience the reality of distributed workplaces incorporating both flexibility and ‘real’ time responsiveness. Students are responsible and accountable for individual and group work contributions in a highly transparent and readily accessible workspace. This experience provides a model of an effective learning tool. Navigating uncertainty and complexity. Collaborative technologies allows students to develop critical thinking and reflective skills as they develop a group product. In this forum students build resilience by taking ownership and managing group work, and navigating the uncertainties and complexities of group dynamics as they constructively and professionally engage in team dialogue and learn to focus on the goal of the team task.

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Purpose: To quantify the uncertainties of carotid plaque morphology reconstruction based on patient-specific multispectral in vivo magnetic resonance imaging (MRI) and their impacts on the plaque stress analysis. Materials and Methods: In this study, three independent investigators were invited to reconstruct the carotid bifurcation with plaque based on MR images from two subjects to study the geometry reconstruction reproducibility. Finite element stress analyses were performed on the carotid bifurcations, as well as the models with artificially modified plaque geometries to mimic the image segmentation uncertainties, to study the impacts of the uncertainties to the stress prediction. Results: Plaque reconstruction reproducibility was generally high in the study. The uncertainties among interobservers are around one or the subpixel level. It also shows that the predicted stress is relatively less sensitive to the arterial wall segmentation uncertainties, and more affected by the accuracy of lipid region definition. For a model with lipid core region artificially increased by adding one pixel on the lipid region boundary, it will significantly increase the maximum Von Mises Stress in fibrous cap (>100%) compared with the baseline model for all subjects. Conclusion: The current in vivo MRI in the carotid plaque could provide useful and reliable information for plaque morphology. The accuracy of stress analysis based on plaque geometry is subject to MRI quality. The improved resolution/quality in plaque imaging with newly developed MRI protocols would generate more realistic stress predictions.

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The energy, position, and momentum eigenstates of a para-Bose oscillator system were considered in paper I. Here we consider the Bargmann or the analytic function description of the para-Bose system. This brings in, in a natural way, the coherent states ||z;alpha> defined as the eigenstates of the annihilation operator ?. The transformation functions relating this description to the energy, position, and momentum eigenstates are explicitly obtained. Possible resolution of the identity operator using coherent states is examined. A particular resolution contains two integrals, one containing the diagonal basis ||z;alpha>and the other containing the pseudodiagonal basis ||z;alpha><−z;alpha||. We briefly consider the normal and antinormal ordering of the operators and their diagonal and discrete diagonal coherent state approximations. The problem of constructing states with a minimum value of the product of the position and momentum uncertainties and the possible alpha dependence of this minimum value is considered. Journal of Mathematical Physics is copyrighted by The American Institute of Physics.