000 | 03645nam a22005055i 4500 | ||
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001 | 978-3-540-78879-9 | ||
003 | DE-He213 | ||
005 | 20140220083740.0 | ||
007 | cr nn 008mamaa | ||
008 | 101120s2011 gw | s |||| 0|eng d | ||
020 |
_a9783540788799 _9978-3-540-78879-9 |
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024 | 7 |
_a10.1007/978-3-540-78879-9 _2doi |
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050 | 4 | _aTJ210.2-211.495 | |
050 | 4 | _aTJ163.12 | |
072 | 7 |
_aTJFM _2bicssc |
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_aTJFD _2bicssc |
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_aTEC004000 _2bisacsh |
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072 | 7 |
_aTEC037000 _2bisacsh |
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082 | 0 | 4 |
_a629.8 _223 |
100 | 1 |
_aIsermann, Rolf. _eauthor. |
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245 | 1 | 0 |
_aIdentification of Dynamic Systems _h[electronic resource] : _bAn Introduction with Applications / _cby Rolf Isermann, Marco Münchhof. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2011. |
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300 |
_aXXV, 705 p. 268 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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520 | _aPrecise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators, machine tools, industrial robots, pumps, vehicles to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the nonparametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing. | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aComputer simulation. | |
650 | 0 | _aPhysics. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aControl, Robotics, Mechatronics. |
650 | 2 | 4 | _aComplexity. |
650 | 2 | 4 | _aCalculus of Variations and Optimal Control, Optimization. |
650 | 2 | 4 | _aSimulation and Modeling. |
650 | 2 | 4 | _aNumerical and Computational Physics. |
700 | 1 |
_aMünchhof, Marco. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783540788782 |
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-540-78879-9 |
912 | _aZDB-2-ENG | ||
999 |
_c106658 _d106658 |