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130626 ||| eng |
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|a 9780857298232
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|a Robinett III, Rush D.
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| 245 |
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|a Nonlinear Power Flow Control Design
|h Elektronische Ressource
|b Utilizing Exergy, Entropy, Static and Dynamic Stability, and Lyapunov Analysis
|c by Rush D. Robinett III, David G. Wilson
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| 250 |
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|a 1st ed. 2011
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| 260 |
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|a London
|b Springer London
|c 2011, 2011
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| 300 |
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|a XXXIV, 346 p. 260 illus., 147 illus. in color
|b online resource
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|a Part I: Theory -- Introduction -- Thermodynamics -- Mechanics -- Stability -- Advanced Control Design -- Part II: Applications: Case Studies -- Case Study 1: Control Design Issues -- Case Study2: Collective Plume Tracing: A Minimal Information Approach to Collective Control -- Case Study 3: Nonlinear Aeroelasticity -- Case Study 4: Fundamental Power Engineering -- Case Study#5: Renewable Energy Microgrid Design -- Case Study 6: Robotic Manipulator Design and Control -- Case Study 7: Satellite Rendezvous and Docking Control -- Case Study 8: Other -- Part III: Advanced Topics -- Sustainability of Self-organizing Systems -- Analytical Model of a Person and Teams: Control System Approach
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| 653 |
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|a Renewable Energy
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| 653 |
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|a Heat engineering
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| 653 |
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|a Electric power production
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| 653 |
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|a Control, Robotics, Automation
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| 653 |
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|a Thermodynamics
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| 653 |
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|a Applied Dynamical Systems
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| 653 |
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|a Heat transfer
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| 653 |
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|a Nonlinear theories
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| 653 |
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|a Control engineering
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| 653 |
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|a Telecommunication
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| 653 |
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|a Robotics
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| 653 |
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|a Electrical Power Engineering
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| 653 |
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|a Renewable energy sources
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| 653 |
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|a Communications Engineering, Networks
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| 653 |
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|a Mass transfer
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| 653 |
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|a Engineering Thermodynamics, Heat and Mass Transfer
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| 653 |
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|a Automation
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| 653 |
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|a Dynamics
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| 700 |
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|a Wilson, David G.
|e [author]
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
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|a Understanding Complex Systems
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| 028 |
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|a 10.1007/978-0-85729-823-2
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| 856 |
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|u https://doi.org/10.1007/978-0-85729-823-2?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 621.042
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| 520 |
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|a Nonlinear Powerflow Control Design presents an innovative control system design process motivated by renewable energy electric grid integration problems. The concepts developed result from the convergence of three research and development goals: • to create a unifying metric to compare the value of different energy sources – coal-burning power plant, wind turbines, solar photovoltaics, etc. – to be integrated into the electric power grid and to replace the typical metric of costs/profit; • to develop a new nonlinear control tool that applies power flow control, thermodynamics, and complex adaptive systems theory to the energy grid in a consistent way; and • to apply collective robotics theories to the creation of high-performance teams of people and key individuals in order to account for human factors in controlling and selling power into a distributed, decentralized electric power grid.
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|a Highlights of several of the case studies feature current renewable energy problems such as the future of electric power grid control, wind turbine load alleviation, and novel controldesigns for micro-grids that incorporate wind and sunlight as renewable energy sources. The sustainability of self-organizing systems are dealt with as advanced topics. Research scientists, practicing engineers, engineering students, and others with a background in engineering will be able to develop and apply this methodology to their particular problems
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|a All three of these goals have important concepts in common: exergy flow, limit cycles, and balance between competing power flows. In place of the typical zero-sum, stability vs. performance, linear controller design process, the authors propose a unique set of criteria to design controllers for a class of nonlinear systems with respect to both performance and stability, and seamlessly integrating information theoretic concepts. A combination of thermodynamics with Hamiltonian systems provides the theoretical foundation which is then realized in a series of connected case studies. It allows the process of control design to be viewed as a power flow control problem, balancing the power flowing into a system against that being dissipated within it and dependent on the power being stored in it – an interplay between kinetic and potential energies.
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