954 resultados para Convergence Analysis


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In this work, we proposes a control strategy that allows the remote manipulator follow the local manipulator through the state convergence even if it has a delay in the communication channel. The bilateral control of the teleoperator system considers the case were the human operator applies a constant force on the local manipulator and when the interaction of the remote manipulator with the environment is considered passive. The stability analysis was performed using Lyapunov- Krasovskii functional, it showed for the case with constant delay, that using a proposed control algorithm by state convergence resulted in asymptotically stable, local and remote the nonlinear teleoperation system.

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In this work, we proposes a control strategy by state convergence applied to bilateral control of a nonlinear teleoperator system with constant delay. The bilateral control of the teleoperator system considers the case when the human operator applies a constant force on the local manipulator and when the interaction of the remote manipulator with the environment is considered passive. The stability analysis is performed using Lyapunov-Krasovskii functional, it showed that using an control algorithm by state convergence for the case with constant delay, the nonlinear local and remote teleoperation system is asymptotically stable, also speeds converge to zero and position tracking is achieved. This work also presents the implementation of an experimental platform. The mechanical structure of the arm that is located in the remote side has been built and the electric servomechanism has been mounted to control their movement.

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This paper examines the participation of the European Union (EU) in the multilateral negotiations of the UN Arms Trade Treaty (ATT). Given the EU’s declared commitment to effective multilateralism and dedication to act as a global security provider, the paper analyses to what extent the EU can be seen as an effective actor in supporting and promoting the ATT. It is argued that overall the EU was an effective player during the multilateral negotiations on the ATT, but the degree of its effectiveness varied along different dimensions. The EU was relatively successful in the achievement of its goals and in maintaining external cohesion during the negotiations, but it scored relatively low in its efforts to commit other major players to sign up to the ATT. The high level of institutional cooperation and the convergence of EU member states’ interests facilitated the EU’s effectiveness in the ATT negotiations, whereas the international context proved to be the major constraining factor.

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This paper theorizes about the convergence of international organizations in global health governance, a field of international cooperation that is commonly portrayed as particularly hit by institutional fragmentation. Unlike existing theories on interorganizationalism that have mainly looked to intra- and extraorganizational factors in order to explain why international organizations cooperate with each other in the first place, the paper is interested in the link between causes and systemic effects of interorganizational convergence. The paper begins by defining interorganizational convergence. It then proceeds to discuss why conventional theories on interorganizational- ism fail to explain the aggregate effects of convergence between IOs in global (health) governance which tend to worsen rather than cushion fragmentation — so-called "hypercollective action" (Severino & Ray 2010). In order to remedy this explanatory blind-spot the paper formulates an alternative sociological institutionalist theory on interorganizational convergence that makes two core theoretical propositions: first that emerging norms of metagovernance are a powerful driver behind interorganizational convergence in global health governance, and secondly that IOs are engaged in a fierce meaning-struggle over these norms which results in hypercollective action. In its empirical part, the paper’s core theoretical propositions are corroborated by analyzing discourses and practices of interorganizational convergence in global health. The empirical analysis allows drawing two far-reaching conclusions. On the one hand, interorganizational harmonization has emerged as a largely undisputed norm in global health which has been translated into ever more institutionalized forms of interorganizational cooperation. On the other, discourses and practices of interorganizational harmonization exhibit conflicts over the ordering principles according to which the policies and actions of international organizations with overlapping mandates and missions should be harmonized. In combination, these two empirical findings explain why interorganizational convergence has so far failed to strengthen the global health architecture.

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India’s success story in services is well documented at the national level, but similar literature does not exist for India’s states. In this paper, we bridge this gap in research by looking at India’s services growth at the sub-national level and in doing so, also challenge existing literature by arguing that this growth has positive implications for income distribution. We find that even as per capita income is not converging across India’s states, per capita services are; evidence is provided both in terms of traditional measures of sigma- and beta-convergence and more recent panel unit root tests. A more disaggregated analysis of services sectors reveals convergence in railways, public administration and financial services. Finally, a Jensen & Kletzer (2005) approach to determining tradability provides evidence of most services being “traded” across India’s states, suggesting the role of such trade in the services growth and convergence story.

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Includes bibliographical references.

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Let (Phi(t))(t is an element of R+) be a Harris ergodic continuous-time Markov process on a general state space, with invariant probability measure pi. We investigate the rates of convergence of the transition function P-t(x, (.)) to pi; specifically, we find conditions under which r(t) vertical bar vertical bar P-t (x, (.)) - pi vertical bar vertical bar -> 0 as t -> infinity, for suitable subgeometric rate functions r(t), where vertical bar vertical bar - vertical bar vertical bar denotes the usual total variation norm for a signed measure. We derive sufficient conditions for the convergence to hold, in terms of the existence of suitable points on which the first hitting time moments are bounded. In particular, for stochastically ordered Markov processes, explicit bounds on subgeometric rates of convergence are obtained. These results are illustrated in several examples.

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Multi-agent systems are complex systems comprised of multiple intelligent agents that act either independently or in cooperation with one another. Agent-based modelling is a method for studying complex systems like economies, societies, ecologies etc. Due to their complexity, very often mathematical analysis is limited in its ability to analyse such systems. In this case, agent-based modelling offers a practical, constructive method of analysis. The objective of this book is to shed light on some emergent properties of multi-agent systems. The authors focus their investigation on the effect of knowledge exchange on the convergence of complex, multi-agent systems.

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This study empirically compares and contrasts the cultural value orientations of employees from Poland and Turkey by testing the compatibility of their values in three stages through seven cultural dimensions. The first phase of the study deals with the assessment of inter-country cultural value differences; the second phase investigates the intra-country cultural dynamics between selected demographic groups; and the third phase examines the inter-country cultural differences among the selected demographic groups of employees. The research has been conducted adopting the Maznevski, DiStephano, and Nason's (1995) version of cultural perspectives questionnaire with a sample of 744 (548 Polish and 196 Turkish) respondents. The results show significant cultural differences between Poland and Turkey, a presence of cultural dynamics among certain demographic groups within the country, and a mixture of convergence and divergence in the value systems of certain demographic groups both within and between the two nation(s). The research findings convey important messages to international human resource strategists in order for them to employ an effective and rational employment policy and business negotiation approach(es) to effectively operate in these countries. It also highlights that diversity of cultural values not only requires viewing each of them through cultural dimensions at a macro-level with a cross-country reference, but also requires monitoring their dynamics at the micro-level with reference to controlled demographic groups. © 2013 Taylor & Francis.

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Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

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Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

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2000 Mathematics Subject Classification: 44A15, 44A35, 46E30

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Mathematics Subject Classification: 30B10, 30B30; 33C10, 33C20