38,855 research outputs found
Objectives, stimulus and feedback in signal control of road traffic
No full textThis article identifies the prospective role of a range of intelligent transport systems technologies for the signal control of road traffic. We discuss signal control within the context of traffic management and control in urban road networks and then present a control-theoretic formulation for it that distinguishes the various roles of detector data, objectives of optimization, and control feedback. By reference to this, we discuss the importance of different kinds of variability in traffic flows and review the state of knowledge in respect of control in the presence of different combinations of them. In light of this formulation and review, we identify a range of important possibilities for contributions to traffic management and control through traffic measurement and detection technology, and contemporary flexible optimization techniques that use various kinds of automated learning
Curing Cholera: Pathogens, Places and Poverty in South Asia
No full textIn this paper I will seek to provide a new understanding of endemicity of disease in India. Through a study of cholera research in the twentieth century I will argue that disease and its endemicity has to be understood in biological factors as well as within a wider social and economic context. I will discuss the medical efforts at locating the causality of cholera from the nineteenth century in Indian climate, water bodies and human anatomy to show that cholera is no more a biological phenomena than water is an ecological or environmental problem. Both are essentially political and economic questions
Nonessential functionals in multiobjective optimal control problems
No full textWe address the problem of obtaining well-defined criteria for multiple criteria optimal control problems. Necessary and sufficient conditions for an objective functional to be nonessential are proved. The results provide effective tools for determining nonessential objectives in multiobjective optimal control problems
An Advance Distributed Control Design for Wide-Area Power System Stability
No full textThe development of control of a power system that supply electricity is a major concern in the world. Some trends have led to power systems becoming overstated including the rapid growth in the demand for electrical power, the increasing penetration of the system from renewable energy, and uncertainties in power schedules and transfers. To deal with these challenges, power control has to overcome several structural hurdles, a major one of which is dealing with the high dimensionality of the system.
Dimensionality reduction of the controller structure produces effective control signals with reduced computational load. In most of the existing studies, the topology of the control and communication structure is known prior to synthesis, and the design of distributed control is performed subject to this particular structure. However, in this thesis we present an advanced model of design for distributed control in which the control systems and their communication structure are designed simultaneously. In such cases, a structure optimization problem is solved involving the incorporation of communication constraints that will punish any communication complexity in the interconnection and thus will be topology dependent. This structure optimization problem can be formulated in the context of Linear Matrix Inequalities and l1-minimization.
Interconnected power systems typically show multiple dominant inter-area low-frequency oscillations which lead to widespread blackouts. In this thesis, the specific goal of stability control is to suppress these inter-area oscillations. Simulation results on large-scale power system are presented to show how an optimal structure of distributed control would be designed. Then, this structure is compared with fixed control structures, a completely decentralized control structure and a centralized control structure
Relationship between genetic-related objectives among state cancer control plans and colorectal cancer incidence and mortality
No full textIntroduction: Colorectal cancer is the third most deadly cancer in the United States and Lynch syndrome (LS) is the most common hereditary colorectal cancer, therefore identifying interventions that reduce the incidence and mortality is a critical public health issue. Current guidelines recommend screening all individuals with newly diagnosed colorectal cancer tumors for LS to reduce morbidity and mortality among relatives. However, states vary in their inclusion of genetic-related strategies in their cancer control plans and the relationship between these strategies and incidence, and incidence-based mortality for LS is unclear.
Methods: I categorized 51 state cancer control plans by five levels of evidence-based genetic strategies. For each state, I obtained incidence and Incidence-based mortality for colorectal cancers diagnosed before age 50 through the National Program of Cancer Registries (NPCR) and Surveillance, Epidemiology, and the End Results (SEER) program from 2001-2015. I next assessed possible relationships between cancer control plan categories and each state’s incidence of colorectal cancer and incidence-based mortality for LS.
Results: Seven states (14%) had no genetics mentioned in their plan, 9 (18%) state plans included a genetics-related term, 13 (25%) plans had a genetics-related objective, 16 (31%) plans had a LS specific objective, and 6 (12%) of state plans had an objective related to screening all individuals with newly diagnosed colorectal cancers for Lynch syndrome. Overall, the inclusion of genetics in a state cancer control plan was not related to colorectal cancer incidence (p=0.90) nor incidence-based mortality (p=0.50) of colorectal cancer diagnosed before age 50.
Conclusion: I observed no relationship between measures of colorectal cancer incidence or mortality and state cancer control plan objectives, most likely because most state cancer plans that incorporated genetic screening were only developed within the past 10 years. However, 68% of states included a genetics-related goal in their cancer control plans. Furthermore, plans developed after 2015 were more likely to include goals related to universal screening, genetic testing, or genetic counseling. Future analyses should focus on evaluating shorter term outcomes such as earlier age of colorectal cancer diagnosis, as well as the number of at-risk individuals identified via cascade screening of relatives
Consensus-based Optimal Control Strategy for Multi-microgrid Systems with Battery Degradation Consideration
No full texthas been widely used in distributed control, where distributed individuals need to share their states with their neighbors through communication links to achieve a common goal. However, the objectives of existing consensus-based control strategies for energy systems seldom address battery degradation cost, which is an important performance indicator to assess the performance and sustainability of battery energy storage (BES) systems. In this paper, we propose a consensusbased optimal control strategy for multi-microgrid systems, aiming at multiple control objectives including minimizing battery degradation cost. Distributed consensus is used to synchronize the ratio of BES output power to BES state-of-charge (SoC) among all microgrids while each microgrid is trying to reach its individual optimality. In order to reduce the pressure of communication links and prevent excessive exposure of local information, this ratio is the only state variable shared between microgrids. Since our complex nonlinear problem might be difficult to solve by traditional methods, we design a compressive sensing-based gradient descent (CSGD) method to solve the control problem. Numerical simulation results show that our control strategy results in a 74.24% reduction in battery degradation cost on average compared to the control method without considering battery degradation. In addition, the compressive sensing method causes an 89.12% reduction in computation time cost compared to the traditional Monte Carlo (MC) method in solving the control problem
Control-theoretic methods for biological networks
No full textFeedback is both a pillar of control theory and a pervasive principle of nature. For this reason, control-theoretic methods are powerful to analyse the dynamic behaviour of biological systems and mathematically explain their properties, as well as to engineer biological systems so that they perform a specific task by design. This paper illustrates the relevance of control-theoretic methods for biological systems. The first part gives an overview of biological control and of the versatile ways in which cells use feedback. By employing control-theoretic methods, the complexity of interlaced feedback loops in the cell can be revealed and explained, and layered feedback loops can be designed in the cell to induce the desired behaviours, such as oscillations, multi-stability and activity regulation. The second part is mainly devoted to modelling uncertainty in biology and understanding the robustness of biological phenomena due to their inherent structure. Important control-theoretic tools used in systems biology are surveyed. The third part is focused on tools for model discrimination in systems biology. A deeper understanding of molecular pathways and feedback loops, as well as qualitative information on biological networks, can be achieved by studying the “dynamic response phenotypes” that appear in temporal responses. Several applications to the analysis of biological systems are showcased.Accepted Author ManuscriptTeam Tamas Keviczk
Nonlinear Multirate Adaptive Control of a Sincronous Motor
No full textThe nonlinear adaptive digital control of a synchronous motor using a nonlinear modelization in the (d, q) frame is discussed. It is shown that a multirate control strategy provides an appropriate framework for achieving speed regulation, thereby ensuring the stability of the whole control system. When parametric uncertainties on the resistance of the stator windings and the load torque occur, this scheme is completed with an adaptation law deduced from hyperstability concepts. This results in the asymptotic satisfaction of the control objectives at the sample instants. Simulation results are presente
An endemic omnivorous predator for control of greenhouse pests
No full textBook Description "Biological control: a global perspective": This book contains 45 chapters divided into four sections, i.e. classical biocontrol programmes, inundative (or augmentative) biocontrol programmes (using nematodes, bacteria, fungi and viruses), conservation biocontrol programmes and networking in biocontrol. It describes the personal experiences of scientists from the initial search for suitable control agents against weeds and pests, to the release of these biological control agents into ecosystems and finally to the beneficial outcomes demonstrating the success of biological control across diverse agroecosystems. This book is intended for researchers and students interested in crop science, pest management, biotechnology, ecology and policy analysis.
Book chapter: Generalist natural enemies can be key members of biological control programmes. We believe that importation of generalist natural enemies for biological control should be avoided, and that endemic natural enemies should be used instead. We summarize our progress developing a generalist mirid, Dicyphus hesperus, for biological control in greenhouse tomato crops. Our success in locating a generalist mirid which can fill a niche in protected culture illustrates the potential for such approaches. This predator satisfies four of five preconditions that we set when we started the project and could potentially be used successfully as part of biological control programmes in greenhouses in North America.book chapterPublished
Morphologic and functional correlates of synaptic pathology in the cathepsin D knockout mouse model of congenital neuronal ceroid lipofuscinosis
No full textMutations in the cathepsin D (CTSD) gene cause an aggressive neurodegenerative disease (congenital neuronal ceroid lipofuscinosis) that leads to early death. Recent evidence suggests that presynaptic abnormalities play a major role in the pathogenesis of CTSD deficiencies. To identify the early events that lead to synaptic alterations, we investigated synaptic ultrastructure and function in presymptomatic CTSD knockout (Ctsd) mice. Electron microscopy revealed that there were significantly greater numbers of readily releasable synaptic vesicles present in Ctsd mice than in wild-type control mice as early as postnatal day 16. The size of this synaptic vesicle pool continued to increase with disease progression in the hippocampus and thalamus of the Ctsd mice. Electrophysiology revealed a markedly decreased frequency of miniature excitatory postsynaptic currents (mEPSCs) with no effect on paired-pulse modulation of the evoked excitatory post synaptic potentials in the hippocampus of Ctsd mice. The reduced mEPSCs frequency was observed before the appearance of epilepsy or any morphologic sign of synaptic degeneration. Taken together, these data indicate that CTSD is required for normal synaptic function and that a failure in synaptic trafficking or recycling may bean early and important pathologic mechanism in Ctsd mice; these presynaptic abnormalities may initiate synaptic degeneration in advance of subsequent neuronal loss
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