135 resultados para time delay systems


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This paper reports on determination of structurally constrained controllers for linear uncertain time-invariant systems from state controllers. It is shown that practical structures such as output and decentralized controllers may be derived from state feedback controllers. A previously studied load frequency control of a two-area interconnected power system is considered to illustrate the proposed approach.


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This paper describes a technique for the real-time modeling of deformable tissue. Specifically geared towards needle insertion simulation, the low computational requirements of the model enable highly accurate haptic feedback to a user without introducing noticeable time delay or buzzing generally associated with haptic surgery simulation. Using a spherical voxel array combined with aspects of computational geometry and agent communication and interaction principals, the model is capable of providing haptic update rates of over 1000Hz with real-time visual feedback. Iterating through over 1000 voxels per millisecond to determine collision and haptic response while making use of Vieta’s Theorem for extraneous force culling.

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Wireless sensor networks represent a new generation of real-time embedded systems with significantly different communication constraints from the traditional networked systems. With their development, a new attack called a path-based DoS (PDoS) attack has appeared. In a PDoS attack, an adversary, either inside or outside the network, overwhelms sensor nodes by flooding a multi-hop end-to-end communication path with either replayed packets or injected spurious packets. Detection and recovery from PDoS attacks have not been given much attention in the literature. In this article, we consider wireless sensor networks designed to collect and store data. In a path-based attack, both sensor nodes and the database containing collected data can be compromised. We propose a recovery method using mobile agents which can detect PDoS attacks easily and efficiently and recover the compromised nodes along with the database.

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Restoration of native vegetation is required in many regions of the world, but determining priority locations for revegetation is a complex problem. We consider the problem of determining spatial and temporal priorities for revegetation to maximize habitat for 62 bird species within a heavily cleared agricultural region, 11 000 km2 in area. We show how a reserve-selection framework can be applied to a complex, large-scale restoration-planning problem to account for multi-species objectives and connectivity requirements at a spatial extent and resolution relevant to management. Our approach explicitly accounts for time lags in planting and development of habitat resources, which is intended to avoid future population bottlenecks caused by delayed provision of critical resources, such as tree hollows. We coupled species-specific models of expected habitat quality and fragmentation effects with the dynamics of habitat suitability following replanting to produce species-specific maps for future times. Spatial priorities for restoration were determined by ranking locations (150-m grid cells) by their expected contribution to species habitat through time using the conservation planning tool, ‘‘Zonation.’’ We evaluated solutions by calculating expected trajectories of habitat availability for each species. We produced a spatially explicit revegetation schedule for the region that resulted in a balanced increase in habitat for all species. Priority areas for revegetation generally were clustered around existing vegetation, although not always. Areas on richer soils and with high rainfall were more highly ranked, reflecting their potential to support high-quality habitats that have been disproportionately cleared for agriculture. Accounting for delayed development of habitat resources altered the rank-order of locations in the derived revegetation plan and led to improved expected outcomes for fragmentation-sensitive species. This work demonstrates the potential for systematic restoration planning at large scales that accounts for multiple objectives, which is urgently needed by land and natural resource managers.

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An optimization problem arising in the analysis of controllability and stabilization of cycles in discrete time chaotic systems is considered.

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In this paper we use the modified and integrated version of the balloon model in the analysis of fMRI data. We propose a new state space model realization for this balloon model and represent it with the standard A,B,C and D matrices widely used in system theory. A second order Padé approximation with equal numerator and denominator degree is used for the time delay approximation in the modeling of the cerebral blood flow. The results obtained through numerical solutions showed that the new state space model realization is in close agreement to the actual modified and integrated version of the balloon model. This new system theoretic formulation is likely to open doors to a novel way of analyzing fMRI data with real time robust estimators. With further development and validation, the new model has the potential to devise a generalized measure to make a significant contribution to improve the diagnosis and treatment of clinical scenarios where the brain functioning get altered. Concepts from system theory can readily be used in the analysis of fMRI data and the subsequent synthesis of filters and estimators.

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The design of a minimum-order linear functional observer for linear time-invariant systems has been an open problem for over four decades. This technical note provides a solution to this problem. The technical note also introduces the concept of Functional Observability/Detectability and shows that the well-known concept of Observability/Detectability is a special case of Functional Observability/Detectability.

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Background: Childhood mental health problems are highly prevalent, experienced by one in five children living in socioeconomically disadvantaged families. Although childcare settings, including family day care are ideal to promote children’s social and emotional wellbeing at a population level in a sustainable way, family day care educators receive limited training in promoting children’s mental health. This study is an exploratory wait-list control cluster randomised controlled trial to test the appropriateness, acceptability, cost, and effectiveness of “Thrive,” an intervention program to build the capacity of family day care educators to promote children’s social and emotional wellbeing. Thrive aims to increase educators’ knowledge, confidence and skills in promoting children’s social and emotional wellbeing.
Methods/Design: This study involves one family day care organisation based in a low socioeconomic area of Melbourne. All family day care educators (term used for registered carers who provide care for children for financial reimbursement in the carers own home) are eligible to participate in the study. The clusters for randomisation will be the fieldworkers (n = 5) who each supervise 10-15 educators. The intervention group (field workers and educators) will participate in a variety of intervention activities over 12 months, including workshops; activity exchanges with other educators; and focused discussion about children’s social and emotional wellbeing during field worker visits. The control group will continue with their normal work practice. The intervention will be delivered to the intervention group and then to the control group after a time delay of 15 months post intervention commencement. A baseline survey will be conducted with all consenting educators and field workers (n = ~70) assessing outcomes at the cluster and individual level. The survey will also be administered at one month, six months and 12 months post-intervention commencement. The survey consists of questions measuring perceived levels of knowledge, confidence and skills in promoting children’s social and emotional wellbeing. As much of this intervention will be delivered by field workers, field worker-family day care educator relationships are key to its success and thus supervisor support will also be measured. All educators will also have an in-home quality of care assessment at baseline, one month, six months and 12 months post-intervention commencement. Process evaluation will occur at one month, six months and 12 months post-intervention commencement. Information regarding intervention fidelity and economics will also be assessed in the survey.
Discussion: A capacity building intervention in child mental health promotion for family day care is an essential contribution to research, policy and practice. This initiative is the first internationally, and essential in building an evidence base of interventions in this extremely policy-timely setting.

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Efficient allocation of skilled and non-skilled workers allow a company to improve productivity and usually requires an understanding of personnel capability, operating conditions and resource availability. This paper examines a labour control strategy that optimises labour skill level, utilisation, task execution time and processing error. The proposed controller manages different labour groups in a multiple work cell environment, providing real-time job assignment, as well as guiding and navigation features. These features can be used to enhance the performance of existing MRP-based or Just-In-Time production systems. A discrete event simulation-based manufacturing model has been developed to assess the performance of the labour controller. Experiments conducted for the selected production scenarios have demonstrated a productivity improvement when using the proposed control. A second experiment has shown that when a skilled labour uses the labour controller to guide them through the job, their utilisation also increases. The proposed controller also has potential application in other domains, such as minimising the shopping time at a supermarket

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Witnessing the wide spread of malicious information in large networks, we develop an efficient method to detect anomalous diffusion sources and thus protect networks from security and privacy attacks. To date, most existing work on diffusion sources detection are based on the assumption that network snapshots that reflect information diffusion can be obtained continuously. However, obtaining snapshots of an entire network needs to deploy detectors on all network nodes and thus is very expensive. Alternatively, in this article, we study the diffusion sources locating problem by learning from information diffusion data collected from only a small subset of network nodes. Specifically, we present a new regression learning model that can detect anomalous diffusion sources by jointly solving five challenges, that is, unknown number of source nodes, few activated detectors, unknown initial propagation time, uncertain propagation path and uncertain propagation time delay. We theoretically analyze the strength of the model and derive performance bounds. We empirically test and compare the model using both synthetic and real-world networks to demonstrate its performance.

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Social networks are often inferred from spatial associations, but other parameters like acoustic communication are likely to play a central role in within group interactions. However, it is currently difficult to determine which individual initiates vocalizations, or who responds to whom. To this aim, we designed a method that allows analyzing group vocal network while controlling for spatial networks, by positioning each group member in equidistant individual cages and analyzing continuous vocal interactions semi-automatically. We applied this method to two types of zebra finch groups, composed of either two adult females and two juveniles, or four young adults (juveniles from the first groups). Young often co-occur in the same social group as adults but are likely to have a different social role, which may be reflected in their vocal interactions. Therefore, we tested the hypothesis that the social structure of the group influences the parameters of the group vocal network. We found that groups including juveniles presented periods with higher level of activity than groups composed of young adults. Using two types of analyses (Markov analysis and cross-correlation), we showed that juveniles as well as adults were more likely to respond to individuals of their own age-class (i.e. to call one after another, in terms of turn-taking, and within a short time-window, in terms of time delay). When juveniles turned into adulthood, they showed adult characteristics of vocal patterns. Together our results suggest that vocal behavior changes during ontogeny, and individuals are more strongly connected with individuals of the same age-class within acoustic networks.

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Absolute stability of Lurie control systems with multiple time-delays is studied in this paper. By using extended Lyapunov functionals, we avoid the use of the stability assumption on the main operator and derive improved stability criteria, which are strictly less conservative than the criteria in [2,3].

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This paper is concerned with stochastic stability of a class of nonlinear discrete-time Markovian jump systems with interval time-varying delay and partially unknown transition probabilities. A new weighted summation inequality is first derived. We then employ the newly derived inequality to establish delay-dependent conditions which guarantee the stochastic stability of the system. These conditions are derived in terms of tractable matrix inequalities which can be computationally solved by various convex optimized algorithms. Numerical examples are provided to illustrate the effectiveness of the obtained results.

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This paper deals with the problem of partial state observer design for linear systems that are subject to time delays in the measured output as well as the control input. By choosing a set of appropriate augmented Lyapunov-Krasovskii functionals with a triple-integral term and using the information of both the delayed output and input, a novel approach to design a minimal-order observer is proposed to guarantee that the observer error is ε-convergent with an exponential rate. Existence conditions of such an observer are derived in terms of matrix inequalities for the cases with time delays in both the output and input and with output delay only. Constructive design algorithms are introduced. Numerical examples are provided to illustrate the design procedure, practicality and effectiveness of the proposed observer.