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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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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 monograph is intended for scientists and engineers working in the field of radar and computational electrodynamics. The book content is the result of works by group of authors who represent the scientific school of applied electrodynamics that had been established in the 1960s by Professor I.V. Sukharevsky within the Govorov Military Radiotechnical Academy. Representatives of this school went on studying electromagnetic wave scattering from objects of various nature consequently in Kharkiv Military University, United Scientific Research Institute of Ukrainian Armed Forces, and Kharkiv Ivan Kozhedub University of Air Force"--

Radar --- Electromagnetic waves --- Radar cross sections. --- Radar targets. --- Data processing. --- Scattering. --- Targets, Radar --- Cross sections, Radar --- Radar cross section measurements --- Radar echo areas --- RCS (Radar) --- Signal processing --- Scattering (Physics) --- Detectors --- Electronic systems --- Pulse techniques (Electronics) --- Radio --- Remote sensing --- Electromagnetics and Microwaves --- Communications System Design --- Aerospace Engineering --- ENG --- ElectricalEngineering --- MechanicalEngineering --- SCI-TECH --- STM --- Computational Electrodynamics --- Electromagnetic Scattering Theory --- Electromagnetic Wave Scattering --- Physical Optics Approximation --- Radar Cross-Section Prediction --- Radar Detection Algorithms --- Radar Microwaves --- Radar Recognition Algorithms --- Radar Scattering Computation --- Radar Scattering Software --- RCS Prediction --- Reduction of Radar Observability --- Sergey V. Nechitaylo --- Stealth Technology --- Valery M. Orlenko --- Vitaly A. Vasilets

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Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

polyacrylonitrile-based carbon fiber --- n/a --- coagulation bath --- binder dissolution --- sensitivity analysis --- simulation --- neural networks --- kernel development --- thermodynamics --- phytochemicals --- wave resonance --- natural extracts --- population balance model --- optimization --- vane --- parameter estimation --- grey-box model --- observability --- optimal clustering --- energy --- idling test --- data-mining --- extents --- computational fluid dynamics --- scrap dissolution --- Combined Heat and Power --- dynamic optimization --- scrap melting --- swelling --- engineering --- dry-jet wet spinning process --- fluid bed granulation --- point estimation method --- algebraic modeling language --- Design of Experiments --- costing stopping --- materials --- hydration --- SOS programming --- kinetics --- moisture content --- CHP legislation --- model predictive control --- graph theory --- robust optimization --- dynamic converter modelling --- partial least square regression --- uncertainty --- state decoupling --- utility management --- fluidized bed drying --- reactor coolant pump --- condensation --- wheat germ --- cooking --- maximum wave amplitude --- moving horizon estimation --- gray-box model --- chemistry --- barley --- machine learning --- heat and mass balance --- equality constraints --- porridge --- process model validation --- Pharmaceutical Processes --- mathematical model --- model identification --- Mammalian Cell Culture --- process modeling --- parameter correlation