921 resultados para Reverse self-control problem


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Background: Given the worldwide prevalence of overweight and obesity, there is a clear need for meaningful practical healthy eating advice - not only in relation to food choice, but also on appropriate food portion sizes. As the majority of portion size research to date has been overwhelmingly quantitative in design, there is a clear need to qualitatively explore consumers’ views in order to fully understand how food portion size decisions are made. Using qualitative methodology this present study aimed to explore consumers’ views about factors influencing their portion size selection and consumption and to identify barriers to appropriate portion size control.

Methods: Ten focus groups with four to nine participants in each were formed with a total of 66 persons (aged 19–64 years) living on the island of Ireland. The semi-structured discussions elicited participants’ perceptions of suggested serving size guidance and explored the influence of personal, social and environmental factors on their food portion size consumption. Audiotapes of the discussions were professionally transcribed verbatim, loaded into NVivo 9, and analysed using an inductive thematic analysis procedure.
Results: The rich descriptive data derived from participants highlight that unhealthy portion size behaviors emanate from various psychological, social and behavioral factors. These bypass reflective and deliberative control, and converge to constitute significant barriers to healthy portion size control. Seven significant barriers to healthy portion size control were apparent: (1) lack of clarity and irrelevance of suggested serving size guidance; (2) guiltless eating; (3) lack of self-control over food cues; (4) distracted eating; (5) social pressures; (6) emotional eating rewards;
and (7) quantification habits ingrained from childhood.

Conclusions: Portion size control strategies should empower consumers to overcome these effects so that the consumption of appropriate food portion sizes becomes automatic and habitual.
Keywords: Food portion size, Barriers, Obesity, Consumers, Qualitative study. © 2013 Spence et al.; licensee BioMed Central Ltd

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Multi-vehicle cooperative formation control problem is an important and typical topic of research on multi-agent system. This paper presents a formation stability conjecture to conceive a new methodology for solving the decentralised multi-vehicle formation control problem. It employs the “extension-decomposition-aggregation” scheme to transform the complex multi-agent control problem into a group of sub-problems which is able to be solved conveniently. Based on this methodology, it is proved that if all the individual augmented subsystems can be stabilised by using any approach, the overall formation system is not only asymptotically but also exponentially stable in the sense of Lyapunov within a neighbourhood of the desired formation. Simulation study on 6-DOF aerial vehicles (Aerosonde UAVs) has been performed to verify the achieved formation stability result. The proposed multi-vehicle formation control strategy can be conveniently extended to other cooperative control problems of multi-agent systems.

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This paper proposes a new methodology for solving the unmanned multi-vehicle formation control problem. It employs a unique “extension-decomposition-aggregation” scheme to transform the overall complex formation control problem to a group of sub-problems which work via boundary interactions. The H∞ robust control strategy is applied to design the decentralised formation controllers to reject the interactions and work jointly to maintain the stability of the overall formation. Simulation studies have been performed to verify its performance and effectiveness.

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Os sistemas compartimentais são frequentemente usados na modelação de diversos processos em várias áreas, tais como a biomedicina, ecologia, farmacocinética, entre outras. Na maioria das aplicações práticas, nomeadamente, aquelas que dizem respeito à administração de drogas a pacientes sujeitos a cirurgia, por exemplo, a presença de incertezas nos parâmetros do sistema ou no estado do sistema é muito comum. Ao longo dos últimos anos, a análise de sistemas compartimentais tem sido bastante desenvolvida na literatura. No entanto, a análise da sensibilidade da estabilidade destes sistemas na presença de incertezas tem recebido muito menos atenção. Nesta tese, consideramos uma lei de controlo por realimentação do estado com restrições de positividade e analisamos a sua robustez quando aplicada a sistemas compartimentais lineares e invariantes no tempo com incertezas nos parâmetros. Além disso, para sistemas lineares e invariantes no tempo com estado inicial desconhecido, combinamos esta lei de controlo com um observador do estado e a robustez da lei de controlo resultante também é analisada. O controlo do bloqueio neuromuscular por meio da infusão contínua de um relaxante muscular pode ser modelado como um sistema compartimental de três compartimentos e tem sido objecto de estudo por diversos grupos de investigação. Nesta tese, os nossos resultados são aplicados a este problema de controlo e são fornecidas estratégias para melhorar os resultados obtidos.

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Consideramos o problema de controlo óptimo de tempo mínimo para sistemas de controlo mono-entrada e controlo afim num espaço de dimensão finita com condições inicial e final fixas, onde o controlo escalar toma valores num intervalo fechado. Quando aplicamos o método de tiro a este problema, vários obstáculos podem surgir uma vez que a função de tiro não é diferenciável quando o controlo é bang-bang. No caso bang-bang os tempos conjugados são teoricamente bem definidos para este tipo de sistemas de controlo, contudo os algoritmos computacionais directos disponíveis são de difícil aplicação. Por outro lado, no caso suave o conceito teórico e prático de tempos conjugados é bem conhecido, e ferramentas computacionais eficazes estão disponíveis. Propomos um procedimento de regularização para o qual as soluções do problema de tempo mínimo correspondente dependem de um parâmetro real positivo suficientemente pequeno e são definidas por funções suaves em relação à variável tempo, facilitando a aplicação do método de tiro simples. Provamos, sob hipóteses convenientes, a convergência forte das soluções do problema regularizado para a solução do problema inicial, quando o parâmetro real tende para zero. A determinação de tempos conjugados das trajectórias localmente óptimas do problema regularizado enquadra-se na teoria suave conhecida. Provamos, sob hipóteses adequadas, a convergência do primeiro tempo conjugado do problema regularizado para o primeiro tempo conjugado do problema inicial bang-bang, quando o parâmetro real tende para zero. Consequentemente, obtemos um algoritmo eficiente para a computação de tempos conjugados no caso bang-bang.

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The shifted Legendre orthogonal polynomials are used for the numerical solution of a new formulation for the multi-dimensional fractional optimal control problem (M-DFOCP) with a quadratic performance index. The fractional derivatives are described in the Caputo sense. The Lagrange multiplier method for the constrained extremum and the operational matrix of fractional integrals are used together with the help of the properties of the shifted Legendre orthonormal polynomials. The method reduces the M-DFOCP to a simpler problem that consists of solving a system of algebraic equations. For confirming the efficiency and accuracy of the proposed scheme, some test problems are implemented with their approximate solutions.

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The purposes of this study were: a) to examine the role of personality and selfregulation in the gambling behaviour participation of late adolescents and emerging adults. In particular, the present study examined i f certain personality traits were more prevalent in high-risk gamblers than in young people considered low or at-risk gamblers; and, b) to examine i f the ability to self-regulate helped distinguish differences among the three groups of gamblers (low-risk, at-risk, and high-risk gamblers). A sample of late adolescents and emerging adults (N = 100) attending Brock University, completed a survey that assessed current gambling behaviour (both frequency and consequence experience), personality, self-esteem, and self-regulation. It was found that high-risk gamblers had lower scores on the personality dimensions Emotionality, Conscientiousness (especially on its Prudence facet), and Honesty-Humility (especially on its Fairness, Greed Avoidance, and Modesty facets) than at-risk or low-risk gamblers and higher scores on impulsive sensation seeking and impulsivity than at-risk or low-risk gamblers. Similarly, high-risk gamblers reported lower levels of self-regulation than both at-risk and low-risk gamblers. The findings from this study support past research which suggests that young people who gamble at problematic levels differ on many personality traits and often have more difficulty self-regulating than young people who do not participate at problematic levels. Findings may aid in the development of intervention and prevention programs that utilize specific self-regulation techniques with a young gambling population.

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Every day we make decisions that have repercussions. Sometimes the effects are immediate and intended; other times the effects might be unintended or might not be apparent for years. As parents or educators, part of our role is to support the development of children’s decision-making skills, helping them to develop patterns of adaptive decision-making that will serve them well in their current lives and into the future. Part of successful decision-making involves self-control, a system served by the brain’s executive functions (EF). This involves the ability to put aside immediate reactions and base decisions on a variety of important considerations. Social-cognitive development, the ongoing improvement of the ability to get along with others and to understand others’ emotions, expressions, motivations, and intents, relies, to a large degree, on the same EF systems. The current paper explores the interaction of these two factors (the role of EF in social-cognitive development), explores the research to determine the most effective approaches to improving both factors, and develops a handbook providing activities for educators to use while supporting the growth of both EF and social-cognitive skills. Results of a needs assessment reveal that the majority (59%) of educators surveyed had never used a social skills improvement program in their classrooms, while a full 95% believed that social skills are important or very important for a student’s academic success.

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Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

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This paper considers left-invariant control systems defined on the Lie groups SU(2) and SO(3). Such systems have a number of applications in both classical and quantum control problems. The purpose of this paper is two-fold. Firstly, the optimal control problem for a system varying on these Lie Groups, with cost that is quadratic in control is lifted to their Hamiltonian vector fields through the Maximum principle of optimal control and explicitly solved. Secondly, the control systems are integrated down to the level of the group to give the solutions for the optimal paths corresponding to the optimal controls. In addition it is shown here that integrating these equations on the Lie algebra su(2) gives simpler solutions than when these are integrated on the Lie algebra so(3).

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This paper presents a novel intelligent multiple-controller framework incorporating a fuzzy-logic-based switching and tuning supervisor along with a generalised learning model (GLM) for an autonomous cruise control application. The proposed methodology combines the benefits of a conventional proportional-integral-derivative (PID) controller, and a PID structure-based (simultaneous) zero and pole placement controller. The switching decision between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using a fuzzy-logic-based supervisor, operating at the highest level of the system. The supervisor is also employed to adaptively tune the parameters of the multiple controllers in order to achieve the desired closed-loop system performance. The intelligent multiple-controller framework is applied to the autonomous cruise control problem in order to maintain a desired vehicle speed by controlling the throttle plate angle in an electronic throttle control (ETC) system. Sample simulation results using a validated nonlinear vehicle model are used to demonstrate the effectiveness of the multiple-controller with respect to adaptively tracking the desired vehicle speed changes and achieving the desired speed of response, whilst penalising excessive control action. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

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This note investigates the motion control of an autonomous underwater vehicle (AUV). The AUV is modeled as a nonholonomic system as any lateral motion of a conventional, slender AUV is quickly damped out. The problem is formulated as an optimal kinematic control problem on the Euclidean Group of Motions SE(3), where the cost function to be minimized is equal to the integral of a quadratic function of the velocity components. An application of the Maximum Principle to this optimal control problem yields the appropriate Hamiltonian and the corresponding vector fields give the necessary conditions for optimality. For a special case of the cost function, the necessary conditions for optimality can be characterized more easily and we proceed to investigate its solutions. Finally, it is shown that a particular set of optimal motions trace helical paths. Throughout this note we highlight a particular case where the quadratic cost function is weighted in such a way that it equates to the Lagrangian (kinetic energy) of the AUV. For this case, the regular extremal curves are constrained to equate to the AUV's components of momentum and the resulting vector fields are the d'Alembert-Lagrange equations in Hamiltonian form.

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A technique is derived for solving a non-linear optimal control problem by iterating on a sequence of simplified problems in linear quadratic form. The technique is designed to achieve the correct solution of the original non-linear optimal control problem in spite of these simplifications. A mixed approach with a discrete performance index and continuous state variable system description is used as the basis of the design, and it is shown how the global problem can be decomposed into local sub-system problems and a co-ordinator within a hierarchical framework. An analysis of the optimality and convergence properties of the algorithm is presented and the effectiveness of the technique is demonstrated using a simulation example with a non-separable performance index.

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In industrial practice, constrained steady state optimisation and predictive control are separate, albeit closely related functions within the control hierarchy. This paper presents a method which integrates predictive control with on-line optimisation with economic objectives. A receding horizon optimal control problem is formulated using linear state space models. This optimal control problem is very similar to the one presented in many predictive control formulations, but the main difference is that it includes in its formulation a general steady state objective depending on the magnitudes of manipulated and measured output variables. This steady state objective may include the standard quadratic regulatory objective, together with economic objectives which are often linear. Assuming that the system settles to a steady state operating point under receding horizon control, conditions are given for the satisfaction of the necessary optimality conditions of the steady-state optimisation problem. The method is based on adaptive linear state space models, which are obtained by using on-line identification techniques. The use of model adaptation is justified from a theoretical standpoint and its beneficial effects are shown in simulations. The method is tested with simulations of an industrial distillation column and a system of chemical reactors.