000 | 03109nam a2200301za04500 | ||
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001 | 17422 | ||
008 | 050703s2011 gw eng d | ||
020 | _a9783540788799 99783540788799 | ||
082 |
_a629.8 _b223 |
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100 |
_aIsermann, Rolf. _eauthor. _934944 |
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245 |
_aIdentification of Dynamic Systems _h[electronic resource]: _bAn Introduction with Applications / _cby Rolf Isermann, Marco MAnchhof. |
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300 |
_aXXV, 705 p. 268 illus. _bonline resource. |
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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, vehiclesá 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 |
_aEngineering. _996 |
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650 |
_aEngineering. _996 |
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650 |
_934945 _aCALCULUS OF VARIATIONS AND OPTICALCONTROL, OBTIMIZATION |
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650 |
_934210 _aCOMPLEXITY |
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650 |
_934207 _aPHYSICS |
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650 |
_933950 _aCOMPUTER SIMULATION |
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650 |
_933916 _aSIMULATION AND MODELING |
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650 |
_933610 _aNUMERICAL AND COMPUTATIONAL PHYSICS |
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650 |
_933591 _aCONTROL, ROBOTICS, MECHATRONICS |
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700 |
_aMAnchhof, Marco. _934946 |
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700 |
_eauthor. _934947 |
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710 |
_aSpringerLink (Online service) _9111 |
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856 |
_uhttp://springer.escuelaing.metaproxy.org/book/10.1007/978-3-540-78879-9 _yir a documento _qURL |
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942 |
_2ddc _cCF |
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_c14047 _d14047 |