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Observers are digital algorithms that combine sensor outputs with knowledge of the system to provide results superior to traditional structures, which rely wholly on sensors. Observers have been used in selected industries for years, but most books explain them with complex mathematics. This book uses intuitive discussion, software experiments, and supporting analysis to explain the advantages and disadvantages of observers. If you are working in controls and want to improve your control systems, observers could be the technology you need and this book will give you a clear, thorough explanati
Observers (Control theory). --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Operations Research --- Observers (Control theory) --- Observability (Control theory) --- State estimator (Control theory) --- State observer (Control theory) --- Control theory --- Engineering --- General and Others
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Adaptive control systems. --- Observers (Control theory) --- Observability (Control theory) --- State estimator (Control theory) --- State observer (Control theory) --- Control theory --- Self-adaptive control systems --- Artificial intelligence --- Feedback control systems --- Self-organizing systems
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This 2001 book presents a general theory as well as a constructive methodology to solve 'observation problems', that is, reconstructing the full information about a dynamical process on the basis of partial observed data. A general methodology to control processes on the basis of the observations is also developed. Illustrative but also practical applications in the chemical and petroleum industries are shown. This book is intended for use by scientists in the areas of automatic control, mathematics, chemical engineering and physics.
Observers (Control theory) --- Missing observations (Statistics) --- Data, Missing (Statistics) --- Missing data (Statistics) --- Missing values (Statistics) --- Observations, Missing (Statistics) --- Values, Missing (Statistics) --- Estimation theory --- Multivariate analysis --- Multiple imputation (Statistics) --- Observability (Control theory) --- State estimator (Control theory) --- State observer (Control theory) --- Control theory
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My aim, in writing this monograph, has been to remedy this omission by presenting a comprehensive and unified theory of observers for continuous-time and discrete -time linear systems. The book is intended for post-graduate students and researchers specializing in control systems, now a core subject in a number of disciplines. Forming, as it does, a self-contained volume it should also be of service to control engineers primarily interested in applications, and to mathematicians with some exposure to control problems.
Mathematical control systems --- Feedback control systems. --- Linear systems. --- Observers (Control theory). --- Observers (Control theory) --- Systems, Linear --- Differential equations, Linear --- System theory --- Feedback mechanisms --- Feedback systems --- Automatic control --- Automation --- Discrete-time systems --- Adaptive control systems --- Feedforward control systems --- Observability (Control theory) --- State estimator (Control theory) --- State observer (Control theory) --- Control theory
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This accessible book provides an introduction to the analysis and design of dynamic multiagent networks. Such networks are of great interest in a wide range of areas in science and engineering, including: mobile sensor networks, distributed robotics such as formation flying and swarming, quantum networks, networked economics, biological synchronization, and social networks. Focusing on graph theoretic methods for the analysis and synthesis of dynamic multiagent networks, the book presents a powerful new formalism and set of tools for networked systems. The book's three sections look at foundations, multiagent networks, and networks as systems. The authors give an overview of important ideas from graph theory, followed by a detailed account of the agreement protocol and its various extensions, including the behavior of the protocol over undirected, directed, switching, and random networks. They cover topics such as formation control, coverage, distributed estimation, social networks, and games over networks. And they explore intriguing aspects of viewing networks as systems, by making these networks amenable to control-theoretic analysis and automatic synthesis, by monitoring their dynamic evolution, and by examining higher-order interaction models in terms of simplicial complexes and their applications. The book will interest graduate students working in systems and control, as well as in computer science and robotics. It will be a standard reference for researchers seeking a self-contained account of system-theoretic aspects of multiagent networks and their wide-ranging applications. This book has been adopted as a textbook at the following universities: ? University of Stuttgart, Germany Royal Institute of Technology, Sweden Johannes Kepler University, Austria Georgia Tech, USA University of Washington, USA Ohio University, USA
Network analysis (Planning) --- Multiagent systems --- Agent-based model (Computer software) --- MASs (Multiagent systems) --- Multi-agent systems --- Systems, Multiagent --- Intelligent agents (Computer software) --- Project networks --- Planning --- System analysis --- Graphic methods. --- Mathematical models. --- Mathematical models --- Graphic methods --- Addition. --- Adjacency matrix. --- Algebraic graph theory. --- Algorithm. --- Automorphism. --- Bipartite graph. --- Cardinality. --- Cartesian product. --- Circulant graph. --- Combinatorics. --- Complete graph. --- Computation. --- Connectivity (graph theory). --- Controllability. --- Convex combination. --- Corollary. --- Cycle graph (algebra). --- Cycle space. --- Degree (graph theory). --- Degree matrix. --- Diagonal matrix. --- Diameter. --- Differentiable function. --- Dimension. --- Directed graph. --- Division by zero. --- Dynamical system. --- Eigenvalues and eigenvectors. --- Equilibrium point. --- Estimation. --- Estimator. --- Existential quantification. --- Extremal graph theory. --- Graph (discrete mathematics). --- Graph theory. --- Identity matrix. --- Incidence matrix. --- Information exchange. --- Initial condition. --- Interconnection. --- Iteration. --- Kalman filter. --- Kronecker product. --- LTI system theory. --- LaSalle's invariance principle. --- Laplacian matrix. --- Least squares. --- Line graph. --- Linear map. --- Lipschitz continuity. --- Lyapunov function. --- Lyapunov stability. --- Markov chain. --- Mathematical optimization. --- Matrix exponential. --- Measurement. --- Multi-agent system. --- Nash equilibrium. --- Natural number. --- Network topology. --- Nonnegative matrix. --- Notation. --- Observability. --- Optimal control. --- Optimization problem. --- Pairwise. --- Parameter. --- Path graph. --- Permutation matrix. --- Permutation. --- Positive semidefinite. --- Positive-definite matrix. --- Probability. --- Quantity. --- Random graph. --- Random variable. --- Rate of convergence. --- Requirement. --- Result. --- Robotics. --- Scientific notation. --- Sensor. --- Sign (mathematics). --- Simplicial complex. --- Special case. --- Spectral graph theory. --- Stochastic matrix. --- Strongly connected component. --- Subset. --- Summation. --- Supergraph. --- Symmetric matrix. --- Systems theory. --- Theorem. --- Theory. --- Unit interval. --- Upper and lower bounds. --- Variable (mathematics). --- Vector space. --- Without loss of generality.
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Here is an indispensable text and reference book for anyone interested in a systems approach to environmental studies. It will be useful not only to geographers but also to ecologists and other environmental scientists; planners; economists and other social scientists; philosophers; and applied mathematicians.Bennett and Chorley's book has a number of broad aims: first, to employ the systems approach to provide an interdisciplinary focus on environmental structures and techniques; second, to use this approach to aid in developing the interfacing of social and economic theory with physical and biological theory; and third, to investigate the implications of this interfacing for human response to current environmental dilemmas, and hence to expose the technological and social bases of values which underlie our use of natural resources.Interpreting the "environment" so as to embrace physical, biological, man-made, social, and economic reality, the authors show that the systems approach provides a powerful vehicle for the statement of environmental situations of ever-growing temporal and spatial magnitude, and for reducing the areas of uncertainty in our increasingly complex decision making arenas.Originally published in 1979.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Sociology of environment --- Environmental protection. Environmental technology --- Human ecology. Social biology --- Human ecology --- 573.22 --- 574 --- Ecology --- Environment, Human --- Human beings --- Human environment --- Ecological engineering --- Human geography --- Nature --- The system theory in biology. Levels of organisation of biological systems. --- General ecology. Biocoenology. Hydrobiology. Biogeography --- Social aspects --- Effect of environment on --- Effect of human beings on --- 574 General ecology. Biocoenology. Hydrobiology. Biogeography --- 573.22 The system theory in biology. Levels of organisation of biological systems. --- The system theory in biology. Levels of organisation of biological systems --- Human ecology. --- Accuracy and precision. --- Air pollution. --- Arrow's impossibility theorem. --- Autocorrelation. --- Bayesian. --- Bessel function. --- Big O notation. --- Causality. --- Consideration. --- Control function (econometrics). --- Control variable. --- Counterintuitive. --- Cross-correlation. --- Decision-making. --- Dynamic programming. --- Economic efficiency. --- Economic planning. --- Ecosystem. --- Emergence. --- Environmental determinism. --- Environmental economics. --- Error term. --- Estimation theory. --- Estimation. --- Estimator. --- Explanation. --- Externality. --- Extrapolation. --- Feed forward (control). --- Forecasting. --- Genetic fallacy. --- Heuristic. --- High- and low-level. --- Holism. --- Hypothesis. --- Ideal type. --- Indifference curve. --- Inference. --- Initial condition. --- Input and output (medicine). --- Instrumental variable. --- Interdependence. --- Inverse problem. --- Isoquant. --- Kalman filter. --- Karush–Kuhn–Tucker conditions. --- Kriging. --- Lag operator. --- Laplace transform. --- Least squares. --- Loss function. --- Marginal rate of substitution. --- Mathematical optimization. --- Maximum likelihood estimation. --- Measurement. --- Natural environment. --- Natural justice. --- Negative feedback. --- Non-renewable resource. --- Nonlinear system. --- Normal conditions. --- Nutrient. --- Observability. --- Optimal control. --- PID controller. --- Parameter. --- Pareto efficiency. --- Partial autocorrelation function. --- Pollutant. --- Pollution. --- Prediction. --- Preference (economics). --- Probability. --- Production–possibility frontier. --- Quantity. --- Result. --- Scarcity. --- Self-tuning. --- Sensitivity analysis. --- Servomechanism. --- Setpoint (control system). --- Simulation. --- Soil. --- Special case. --- State of nature. --- State variable. --- Steady state. --- Stepwise regression. --- Stochastic control. --- Subsidy. --- Supply (economics). --- Surplus value. --- System analysis. --- Tax. --- Theory. --- Time series. --- Transfer function. --- Uncertainty. --- Utility. --- Weighting.
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