Decentralized Estimation Using Conservative Information Extraction

Author : Robin Forsling
Publisher : Linköping University Electronic Press
ISBN 13 : 9179297242
Total Pages : 110 pages
Book Rating : 4.44/5 ( download)

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Download or read book Decentralized Estimation Using Conservative Information Extraction written by Robin Forsling and published by Linköping University Electronic Press. This book was released on 2020-12-17 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensor networks consist of sensors (e.g., radar and cameras) and processing units (e.g., estimators), where in the former information extraction occurs and in the latter estimates are formed. In decentralized estimation information extracted by sensors has been pre-processed at an intermediate processing unit prior to arriving at an estimator. Pre-processing of information allows for the complexity of large systems and systems-of-systems to be significantly reduced, and also makes the sensor network robust and flexible. One of the main disadvantages of pre-processing information is that information becomes correlated. These correlations, if not handled carefully, potentially lead to underestimated uncertainties about the calculated estimates. In conservative estimation the unknown correlations are handled by ensuring that the uncertainty about an estimate is not underestimated. If this is ensured the estimate is said to be conservative. Neglecting correlations means information is double counted which in worst case implies diverging estimates with fatal consequences. While ensuring conservative estimates is the main goal, it is desirable for a conservative estimator, as for any estimator, to provide an error covariance which is as small as possible. Application areas where conservative estimation is relevant are setups where multiple agents cooperate to accomplish a common objective, e.g., target tracking, surveillance and air policing. The first part of this thesis deals with theoretical matters where the conservative linear unbiased estimation problem is formalized. This part proposes an extension of classical linear estimation theory to the conservative estimation problem. The conservative linear unbiased estimator (CLUE) is suggested as a robust and practical alternative for estimation problems where the correlations are unknown. Optimality criteria for the CLUE are provided and further investigated. It is shown that finding an optimal CLUE is more complicated than finding an optimal linear unbiased estimator in the classical version of the problem. To simplify the problem, a CLUE that is optimal under certain restrictions will also be investigated. The latter is named restricted best CLUE. An important result is a theorem that gives a closed form solution to a restricted best CLUE. Furthermore, several conservative estimation methods are described followed by an analysis of their properties. The methods are shown to be conservative and optimal under different assumptions about the underlying correlations. The second part of the thesis focuses on practical aspects of the conservative approach to decentralized estimation in configurations where the communication channel is constrained. The diagonal covariance approximation is proposed as a data reduction technique that complies with the communication constraints and if handled correctly can be shown to preserve conservative estimates. Several information selection methods are derived that can reduce the amount of data being transmitted in the communication channel. Using the information selection methods it is possible to decide what information other actors of the sensor network find useful.

Author : Magnus Malmström
Publisher : Linköping University Electronic Press
ISBN 13 : 9179296807
Total Pages : 103 pages
Book Rating : 4.03/5 ( download)

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Download or read book Uncertainties in Neural Networks written by Magnus Malmström and published by Linköping University Electronic Press. This book was released on 2021-04-06 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: In science, technology, and engineering, creating models of the environment to predict future events has always been a key component. The models could be everything from how the friction of a tire depends on the wheels slip to how a pathogen is spread throughout society. As more data becomes available, the use of data-driven black-box models becomes more attractive. In many areas they have shown promising results, but for them to be used widespread in safety-critical applications such as autonomous driving some notion of uncertainty in the prediction is required. An example of such a black-box model is neural networks (NNs). This thesis aims to increase the usefulness of NNs by presenting an method where uncertainty in the prediction is obtained by linearization of the model. In system identification and sensor fusion, under the condition that the model structure is identifiable, this is a commonly used approach to get uncertainty in the prediction from a nonlinear model. If the model structure is not identifiable, such as for NNs, the ambiguities that cause this have to be taken care of in order to make the approach applicable. This is handled in the first part of the thesis where NNs are analyzed from a system identification perspective, and sources of uncertainty are discussed. Another problem with data-driven black-box models is that it is difficult to know how flexible the model needs to be in order to correctly model the true system. One solution to this problem is to use a model that is more flexible than necessary to make sure that the model is flexible enough. But how would that extra flexibility affect the uncertainty in the prediction? This is handled in the later part of the thesis where it is shown that the uncertainty in the prediction is bounded from below by the uncertainty in the prediction of the model with lowest flexibility required for representing true system accurately. In the literature, many other approaches to handle the uncertainty in predictions by NNs have been suggested, of which some are summarized in this work. Furthermore, a simulation and an experimental studies inspired by autonomous driving are conducted. In the simulation study, different sources of uncertainty are investigated, as well as how large the uncertainty in the predictions by NNs are in areas without training data. In the experimental study, the uncertainty in predictions done by different models are investigated. The results show that, compared to existing methods, the linearization method produces similar results for the uncertainty in predictions by NNs. An introduction video is available at https://youtu.be/O4ZcUTGXFN0 Inom forskning och utveckling har det har alltid varit centralt att skapa modeller av verkligheten. Dessa modeller har bland annat använts till att förutspå framtida händelser eller för att styra ett system till att bete sig som man önskar. Modellerna kan beskriva allt från hur friktionen hos ett bildäck påverkas av hur mycket hjulen glider till hur ett virus kan sprida sig i ett samhälle. I takt med att mer och mer data blir tillgänglig ökar potentialen för datadrivna black-box modeller. Dessa modeller är universella approximationer vilka ska kunna representera vilken godtycklig funktion som helst. Användningen av dessa modeller har haft stor framgång inom många områden men för att verkligen kunna etablera sig inom säkerhetskritiska områden såsom självkörande farkoster behövs en förståelse för osäkerhet i prediktionen från modellen. Neuronnät är ett exempel på en sådan black-box modell. I denna avhandling kommer olika sätt att tillförskaffa sig kunskap om osäkerhet i prediktionen av neuronnät undersökas. En metod som bygger på linjärisering av modellen för att tillförskaffa sig osäkerhet i prediktionen av neuronnätet kommer att presenteras. Denna metod är välbeprövad inom systemidentifiering och sensorfusion under antagandet att modellen är identifierbar. För modeller såsom neuronnät, vilka inte är identifierbara behövs det att det tas hänsyn till tvetydigheterna i modellen. En annan utmaning med datadrivna black-box modeller, är att veta om den valda modellmängden är tillräckligt generell för att kunna modellera det sanna systemet. En lösning på detta problem är att använda modeller som har mer flexibilitet än vad som behövs, det vill säga en överparameteriserad modell. Men hur påverkas osäkerheten i prediktionen av detta? Detta är något som undersöks i denna avhandling, vilken visar att osäkerheten i den överparameteriserad modellen kommer att vara begränsad underifrån av modellen med minst flexibilitet som ändå är tillräckligt generell för att modellera det sanna systemet. Som avslutning kommer dessa resultat att demonstreras i både en simuleringsstudie och en experimentstudie inspirerad av självkörande farkoster. Fokuset i simuleringsstudien är hur osäkerheten hos modellen är i områden med och utan tillgång till träningsdata medan experimentstudien fokuserar på jämförelsen mellan osäkerheten i olika typer av modeller.Resultaten från dessa studier visar att metoden som bygger på linjärisering ger liknande resultat för skattningen av osäkerheten i prediktionen av neuronnät, jämfört med existerande metoder.

Author : Daniel Arnström
Publisher : Linköping University Electronic Press
ISBN 13 : 9179296920
Total Pages : 45 pages
Book Rating : 4.26/5 ( download)

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Download or read book On Complexity Certification of Active-Set QP Methods with Applications to Linear MPC written by Daniel Arnström and published by Linköping University Electronic Press. This book was released on 2021-03-03 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: In model predictive control (MPC) an optimization problem has to be solved at each time step, which in real-time applications makes it important to solve these efficiently and to have good upper bounds on worst-case solution time. Often for linear MPC problems, the optimization problem in question is a quadratic program (QP) that depends on parameters such as system states and reference signals. A popular class of methods for solving such QPs is active-set methods, where a sequence of linear systems of equations is solved. The primary contribution of this thesis is a method which determines which sequence of subproblems a popular class of such active-set algorithms need to solve, for every possible QP instance that might arise from a given linear MPC problem (i.e, for every possible state and reference signal). By knowing these sequences, worst-case bounds on how many iterations, floating-point operations and, ultimately, the maximum solution time, these active-set algorithms require to compute a solution can be determined, which is of importance when, e.g, linear MPC is used in safety-critical applications. After establishing this complexity certification method, its applicability is extended by showing how it can be used indirectly to certify the complexity of another, efficient, type of active-set QP algorithm which reformulates the QP as a nonnegative least-squares method. Finally, the proposed complexity certification method is extended further to situations when enhancements to the active-set algorithms are used, namely, when they are terminated early (to save computations) and when outer proximal-point iterations are performed (to improve numerical stability).

Author : Matthias Hemmje
Publisher : Springer Science & Business Media
ISBN 13 : 3540245510
Total Pages : 341 pages
Book Rating : 4.13/5 ( download)

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Download or read book From Integrated Publication and Information Systems to Information and Knowledge Environments written by Matthias Hemmje and published by Springer Science & Business Media. This book was released on 2005-01-31 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes a commemorative volume devoted to Erich J. Neuhold on the occasion of his 65th birthday. The 32 invited reviewed papers presented are written by students and colleagues of Erich Neuhold throughout all periods of his scientific career. The papers are organized in the following topical sections: Database management enabling information systems Semantic Web drivers for advanced information management Securing dynamic media content integration From digital libraries to intelligent knowledge environments Visualization – key to external cognition in virtual information environments From human-computer interaction to human-artefact interaction Domains for virtual information and knowledge environments.

Author : National Intelligence Council
Publisher : Cosimo Reports
ISBN 13 : 9781646794973
Total Pages : 158 pages
Book Rating : 4.74/5 ( download)

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Download or read book Global Trends 2040 written by National Intelligence Council and published by Cosimo Reports. This book was released on 2021-03 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The ongoing COVID-19 pandemic marks the most significant, singular global disruption since World War II, with health, economic, political, and security implications that will ripple for years to come." -Global Trends 2040 (2021) Global Trends 2040-A More Contested World (2021), released by the US National Intelligence Council, is the latest report in its series of reports starting in 1997 about megatrends and the world's future. This report, strongly influenced by the COVID-19 pandemic, paints a bleak picture of the future and describes a contested, fragmented and turbulent world. It specifically discusses the four main trends that will shape tomorrow's world: - Demographics-by 2040, 1.4 billion people will be added mostly in Africa and South Asia. - Economics-increased government debt and concentrated economic power will escalate problems for the poor and middleclass. - Climate-a hotter world will increase water, food, and health insecurity. - Technology-the emergence of new technologies could both solve and cause problems for human life. Students of trends, policymakers, entrepreneurs, academics, journalists and anyone eager for a glimpse into the next decades, will find this report, with colored graphs, essential reading.

Author : Henry Mintzberg
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.05/5 ( download)

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Download or read book The Structuring of Organizations written by Henry Mintzberg and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Synthesizes the empirical literature on organizationalstructuring to answer the question of how organizations structure themselves --how they resolve needed coordination and division of labor. Organizationalstructuring is defined as the sum total of the ways in which an organizationdivides and coordinates its labor into distinct tasks. Further analysis of theresearch literature is neededin order to builda conceptualframework that will fill in the significant gap left by not connecting adescription of structure to its context: how an organization actuallyfunctions. The results of the synthesis are five basic configurations (the SimpleStructure, the Machine Bureaucracy, the Professional Bureaucracy, theDivisionalized Form, and the Adhocracy) that serve as the fundamental elementsof structure in an organization. Five basic parts of the contemporaryorganization (the operating core, the strategic apex, the middle line, thetechnostructure, and the support staff), and five theories of how it functions(i.e., as a system characterized by formal authority, regulated flows, informalcommunication, work constellations, and ad hoc decision processes) aretheorized. Organizations function in complex and varying ways, due to differing flows -including flows of authority, work material, information, and decisionprocesses. These flows depend on the age, size, and environment of theorganization; additionally, technology plays a key role because of itsimportance in structuring the operating core. Finally, design parameters aredescribed - based on the above five basic parts and five theories - that areused as a means of coordination and division of labor in designingorganizational structures, in order to establish stable patterns of behavior.(CJC).

Author :
Publisher :
ISBN 13 :
Total Pages : 2264 pages
Book Rating : 4.16/5 ( download)

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Download or read book The Engineering Index Annual written by and published by . This book was released on 1992 with total page 2264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its creation in 1884, Engineering Index has covered virtually every major engineering innovation from around the world. It serves as the historical record of virtually every major engineering innovation of the 20th century. Recent content is a vital resource for current awareness, new production information, technological forecasting and competitive intelligence. The world?s most comprehensive interdisciplinary engineering database, Engineering Index contains over 10.7 million records. Each year, over 500,000 new abstracts are added from over 5,000 scholarly journals, trade magazines, and conference proceedings. Coverage spans over 175 engineering disciplines from over 80 countries. Updated weekly.

Author :
Publisher :
ISBN 13 :
Total Pages : 1134 pages
Book Rating : 4.95/5 ( download)

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Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1989 with total page 1134 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Ahmad Taher Azar
Publisher : Academic Press
ISBN 13 : 0323859917
Total Pages : 762 pages
Book Rating : 4.12/5 ( download)

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Download or read book Design, Analysis and Applications of Renewable Energy Systems written by Ahmad Taher Azar and published by Academic Press. This book was released on 2021-09-09 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design, Analysis and Applications of Renewable Energy Systems covers recent advancements in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems as conveyed by leading energy systems engineering researchers. The book focuses on present novel solutions for many problems in the field, covering modeling, control theorems and the optimization techniques that will help solve many scientific issues for researchers. Multidisciplinary applications are also discussed, along with their fundamentals, modeling, analysis, design, realization and experimental results. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work. Presents some of the latest innovative approaches to renewable energy systems from the point-of-view of dynamic modeling, system analysis, optimization, control and circuit design Focuses on advances related to optimization techniques for renewable energy and forecasting using machine learning methods Includes new circuits and systems, helping researchers solve many nonlinear problems

Author : Carl Patton
Publisher : Routledge
ISBN 13 : 1317350006
Total Pages : 481 pages
Book Rating : 4.02/5 ( download)

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Download or read book Basic Methods of Policy Analysis and Planning written by Carl Patton and published by Routledge. This book was released on 2015-08-26 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Updated in its 3rd edition, Basic Methods of Policy Analysis and Planning presents quickly applied methods for analyzing and resolving planning and policy issues at state, regional, and urban levels. Divided into two parts, Methods which presents quick methods in nine chapters and is organized around the steps in the policy analysis process, and Cases which presents seven policy cases, ranging in degree of complexity, the text provides readers with the resources they need for effective policy planning and analysis. Quantitative and qualitative methods are systematically combined to address policy dilemmas and urban planning problems. Readers and analysts utilizing this text gain comprehensive skills and background needed to impact public policy.