Identification of dynamic systems: an introduction with applications
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| Main Authors: | , |
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| Format: | Book |
| Language: | English |
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Berlin [u.a.]
Springer
2011
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| Online Access: | Inhaltstext Inhaltsverzeichnis |
| Physical Description: | XXV, 705 S. Ill., graph. Darst. |
| ISBN: | 9783540788782 9783642422676 |
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MARC
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| 100 | 1 | |a Isermann, Rolf |d 1938- |e Verfasser |0 (DE-588)105902845 |4 aut | |
| 245 | 1 | 0 | |a Identification of dynamic systems |b an introduction with applications |c Rolf Isermann ; Marco Münchhof |
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 2011 | |
| 300 | |a XXV, 705 S. |b Ill., graph. Darst. | ||
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IMAGE 1
CONTENTS
1 INTRODUCTION 1
1.1 THEORETICAL AND EXPERIMENTAL MODELING 1
1.2 TASKS AND PROBLEMS FOR THE IDENTIFICATION OF DYNAMIC SYSTEMS 7 1.3
TAXONOMY OF IDENTIFICATION METHODS AND THEIR TREATMENT IN THIS BOOK 12
1.4 OVERVIEW OF IDENTIFICATION METHODS 15
1.4.1 NON-PARAMETRIC MODELS 15
1.4.2 PARAMETRIC MODELS 18
1.4.3 SIGNAL ANALYSIS 19
1.5 EXCITATION SIGNAIS 21
1.6 SPECIAL APPLICATION PROBLEMS 23
1.6.1 NOISE AT THE INPUT 23
1.6.2 IDENTIFICATION OF SYSTEMS WITH MULTIPLE INPUTS OR OUTPUTS . 23
1.7 AREAS OF APPLICATION 24
1.7.1 GAIN INCREASED KNOWLEDGE ABOUT THE PROCESS BEHAVIOR . . . 24
1.7.2 VALIDATION OF THEORETICAL MODELS 25
1.7.3 TUNING OF CONTROLLER PARAMETERS 25
1.7.4 COMPUTER-BASED DESIGN OF DIGITAL CONTROL ALGORITHMS 25 1.7.5
ADAPTIVE CONTROL ALGORITHMS 26
1.7.6 PROCESS SUPERVISION AND FAULT DETECTION 26
1.7.7 SIGNAL FORECAST 26
1.7.8 ON-LINE OPTIMIZATION 28
1.8 BIBLIOGRAPHICAL OVERVIEW 28
PROBLEMS 29
REFERENCES 30
2 MATHEMATICAL MODELS OF LINEAR DYNAMIC SYSTEMS AND STOCHASTIC SIGNALS
33
2. 1 MATHEMATICAL MODELS OF DYNAMIC SYSTEMS FOR CONTINUOUS TIME SIGNALS
33
2.1.1 NON-PARAMETRIC MODELS, DETERMINISTIC SIGNALS 34
BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/1000031055
DIGITALISIERT DURCH
IMAGE 2
CONTENTS
2.1.2 PARAMETRIC MODELS, DETERMINISTIC SIGNALS 37
2.2 MATHEMATICAL MODELS OF DYNAMIC SYSTEMS FOR DISCRETE TIME SIGNALS 39
2.2.1 PARAMETRIC MODELS, DETERMINISTIC SIGNALS 39
2.3 MODELS FOR CONTINUOUS-TIME STOCHASTIC SIGNALS 45
2.3.1 SPECIAL STOCHASTIC SIGNAL PROCESSES 51
2.4 MODELS FOR DISCRETE TIME STOCHASTIC SIGNALS 54
2.5 CHARACTERISTIC PARAMETER DETERMINATION 58
2.5.1 APPROXIMATION BY A FIRST ORDER SYSTEM 59
2.5.2 APPROXIMATION BY A SECOND ORDER SYSTEM 60
2.5.3 APPROXIMATION BY N' H ORDER DELAY WITH EQUAL TIME CONSTANTS 63
2.5.4 APPROXIMATION BY FIRST ORDER SYSTEM WITH DEAD TIME 68 2.6 SYSTEMS
WITH INTEGRAL OR DERIVATIVE ACTION 69
2.6.1 INTEGRAL ACTION 69
2.6.2 DERIVATIVE ACTION 70
2.7 SUMMARY 71
PROBLEMS 71
REFERENCES 72
PART I IDENTIFICATION OF NON-PARAMETRIC MODELS IN THE FREQUENCY DOMAIN -
CONTINUOUS TIME SIGNALS
3 SPECTRAL ANALYSIS METHODS FOR PERIODIC AND NON-PERIODIC SIGNALS .
77 3. 1 NUMERICAL CALCULATION OF THE FOURIER TRANSFORM 77
3.1.1 FOURIER SERIES FOR PERIODIC SIGNALS 77
3.1.2 FOURIER TRANSFORM FOR NON-PERIODIC SIGNALS 78
3.1.3 NUMERICAL CALCULATION OF THE FOURIER TRANSFORM 82 3.1.4 WINDOWING
88
3.1.5 SHORT TIME FOURIER TRANSFORM 89
3.2 WAVELET TRANSFORM 91
3.3 PERIODOGRAM 93
3.4 SUMMARY 95
PROBLEMS 96
REFERENCES 97
4 FREQUENCY RESPONSE MEASUREMENT WITH NON-PERIODIC SIGNALS 99 4. 1
FUNDAMENTAL EQUATIONS 99
4.2 FOURIER TRANSFORM OF NON-PERIODIC SIGNALS 100
4.2.1 SIMPLE PULSES 100
4.2.2 DOUBLE PULSE 104
4.2.3 STEP AND RAMP FUNCTION 106
4.3 FREQUENCY RESPONSE DETERMINATION 108
4.4 INFLUENCE OF NOISE 109
4.5 SUMMARY 117
IMAGE 3
CONTENTS XI
PROBLEMS 119
REFERENCES 119
FREQUENCY RESPONSE MEASUREMENT FOR PERIODIC TEST SIGNALS 121 5.1
FREQUENCY RESPONSE MEASUREMENT WITH SINUSOIDAL TEST SIGNALS . . 122 5.2
FREQUENCY RESPONSE MEASUREMENT WITH RECTANGULAR AND TRAPEZOIDAL TEST
SIGNALS 124
5.3 FREQUENCY RESPONSE MEASUREMENT WITH MULTI-FREQUENCY TEST SIGNALS 126
5.4 FREQUENCY RESPONSE MEASUREMENT WITH CONTINUOUSLY VARYING FREQUENCY
TEST SIGNALS 128
5.5 FREQUENCY RESPONSE MEASUREMENT WITH CORRELATION FUNCTIONS 129 5.5.1
MEASUREMENT WITH CORRELATION FUNCTIONS 129
5.5.2 MEASUREMENT WITH ORTHOGONAL CORRELATION 134
5.6 SUMMARY 144
PROBLEMS 144
REFERENCES 144
PART II IDENTIFICATION OF NON-PARAMETRIC MODELS WITH CORRELATION
ANALYSIS - CONTINUOUS AND DISCRETE TIME
6 CORRELATION ANALYSIS WITH CONTINUOUS TIME MODELS 149
6.1 ESTIMATION OF CORRELATION FUNCTIONS 149
6.1.1 CROSS-CORRELATION FUNCTION 150
6.1.2 AUTO-CORRELATION FUNCTION 153
6.2 CORRELATION ANALYSIS OF DYNAMIC PROCESSES WITH STATIONARY STOCHASTIC
SIGNAIS 154
6.2.1 DETERMINATION OF IMPULSE RESPONSE BY DECONVOLUTION 154 6.2.2 WHITE
NOISE AS INPUT SIGNAL 157
6.2.3 ERROR ESTIMATION 158
6.2.4 REAL NATURAL NOISE AS INPUT SIGNAL 161
6.3 CORRELATION ANALYSIS OF DYNAMIC PROCESSES WITH BINARY STOCHASTIC
SIGNAIS 161
6.4 CORRELATION ANALYSIS IN CLOSED-LOOP 175
6.5 SUMMARY 176
PROBLEMS 177
REFERENCES 1 77
7 CORRELATION ANALYSIS WITH DISCRETE TIME MODELS 179
7. 1 ESTIMATION OF THE CORRELATION FUNCTION 179
7.1.1 AUTO-CORRELATION FUNCTION 179
7.1.2 CROSS-CORRELATION FUNCTION 181
7.1.3 FAST CALCULATION OF THE CORRELATION FUNCTIONS 184
7.1.4 RECURSIVE CORRELATION 189
IMAGE 4
XII CONTENTS
7.2 CORRELATION ANALYSIS OF LINEAR DYNAMIC SYSTEMS 190
7.2.1 DETERMINATION OF IMPULSE RESPONSE BY DE-CONVOLUTION . . . 190
7.2.2 INFLUENCE OF STOCHASTIC DISTURBANCES 195
7.3 BINARY TEST SIGNALS FOR DISCRETE TIME 197
7.4 SUMMARY 199
PROBLEMS 199
REFERENCES 200
PART III IDENTIFICATION WITH PARAMETRIC MODELS - DISCRETE TIME SIGNALS
8 LEAST SQUARES PARAMETER ESTIMATION FOR STATTE PROCESSES 203 8.1
INTRODUCTION 203
8.2 LINEAR STATIC PROCESSES 205
8.3 NON-LINEAR STATIC PROCESSES 210
8.4 GEOMETRICAL INTERPRETATION 212
8.5 MAXIMUM LIKELIHOOD AND THE CRAMER-RAO BOUND 215
8.6 CONSTRAINTS 218
8.7 SUMMARY 218
PROBLEMS 219
REFERENCES 220
9 LEAST SQUARES PARAMETER ESTIMATION FOR DYNAMIC PROCESSES 223 9. 1
NON-RECURSIVE METHOD OF LEAST SQUARES (LS) 223
. 1 FUNDAMENTAL EQUATIONS 223
.2 CONVERGENCE 229
.3 COVARIANCE OF THE PARAMETER ESTIMATES AND MODEL UNCERTAINTY 236
.4 PARAMETER IDENTIFIABILITY 246
9.1.5 UNKNOWN DC VALUES 255
9.2 SPECTRAL ANALYSIS WITH PERIODIC PARAMETRIC SIGNAL MODELS 257 9.2.1
PARAMETRIC SIGNAL MODELS IN THE TIME DOMAIN 257
9.2.2 PARAMETRIC SIGNAL MODELS IN THE FREQUENCY DOMAIN 258 9.2.3
DETERMINATION OF THE COEFFICIENTS 259
9.2.4 ESTIMATION OF THE AMPLITUDES 261
9.3 PARAMETER ESTIMATION WITH NON-PARAMETRIC INTERMEDIATE M O D E L . .
. 262 9.3.1 RESPONSE TO NON-PERIODIC EXCITATION AND METHOD OF LEAST
SQUARES 262
9.3.2 CORRELATION ANALYSIS AND METHOD OF LEAST SQUARES (COR-LS) 264
9.4 RECURSIVE METHODS OF LEAST SQUARES (RLS) 269
9.4.1 FUNDAMENTAL EQUATIONS 270
9.4.2 RECURSIVE PARAMETER ESTIMATION FOR STOCHASTIC SIGNALS 276 9.4.3
UNKNOWN DC VALUES 278
9.5 METHOD OF WEIGHTED LEAST SQUARES (WLS) 279
IMAGE 5
CONTENTS XIII
9.5.1 MARKOV ESTIMATION 279
9.6 RECURSIVE PARAMETER ESTIMATION WITH EXPONENTIAL FORGETTING 281 9.6.1
CONSTRAINTS AND THE RECURSIVE METHOD OF LEAST SQUARES . . . 283 9.6.2
TIKHONOV REGULARIZARON 284
9.7 SUMMARY 284
PROBLEMS 285
REFERENCES 287
10 MODIFICATIONS OF THE LEAST SQUARES PARAMETER ESTIMATION 291 1 0. 1
METHOD OF GENERALIZED LEAST SQUARES (GLS) 291
10.1.1 NON-RECURSIVE METHOD OF GENERALIZED LEAST SQUARES (GLS) 291
10.1.2 RECURSIVE METHOD OF GENERALIZED LEAST SQUARES (RGLS). 294 10.2
METHOD OF EXTENDED LEAST SQUARES (ELS) 295
10.3 METHOD OF BIAS CORRECTION (CLS) 296
10.4 METHOD OF TOTAL LEAST SQUARES (TLS) 297
10.5 INSTRUMENTAL VARIABLES METHOD (IV) 302
10.5.1 NON-RECURSIVE METHOD OF INSTRUMENTAL VARIABLES (IV) 302 10.5.2
RECURSIVE METHOD OF INSTRUMENTAL VARIABLES (RIV) 305 10.6 METHOD OF
STOCHASTIC APPROXIMATION (STA) 306
10.6.1 ROBBINS-MONRO ALGORITHM 306
10.6.2 KIEFER-WOLFOWITZ ALGORITHM 307
10.7 (NORMALIZED) LEAST MEAN SQUARES (NLMS) 310
10.8 SUMMARY 315
PROBLEMS 316
REFERENCES 316
11 BAYES AND MAXIMUM LIKELIHOOD METHODS 319
11.1 BAYES METHOD 319
11.2 MAXIMUM LIKELIHOOD METHOD (ML) 323
11.2.1 NON-RECURSIVE MAXIMUM LIKELIHOOD METHOD 323 11.2.2 RECURSIVE
MAXIMUM LIKELIHOOD METHOD (RML) 328 11.2.3 CRAMER-RAO BOUND AND MAXIMUM
PRECISION 330 11.3 SUMMARY 331
PROBLEMS 331
REFERENCES 332
12 PARAMETER ESTIMATION FOR TIME-VARIANT PROCESSES 335
12.1 EXPONENTIAL FORGETTING WITH CONSTANT FORGETTING FACTOR 335 12.2
EXPONENTIAL FORGETTING WITH VARIABLE FORGETTING FACTOR 340 12.3
MANIPULATION OF COVARIANCE MATRIX 341
12.4 CONVERGENCE OF RECURSIVE PARAMETER ESTIMATION METHODS 343 12.4.1
PARAMETER ESTIMATION IN OBSERVER FORM 345
12.5 SUMMARY 349
PROBLEMS 350
REFERENCES 350
IMAGE 6
XIV CONTENTS
13 PARAMETER ESTIMATION IN CLOSED-LOOP 353
13.1 PROCESS IDENTIFICATION WITHOUT ADDITIONAL TEST SIGNALS 354 13.1.1
INDIRECT PROCESS IDENTIFICATION (CASE A+C+E) 355
13.1.2 DIRECT PROCESS IDENTIFICATION (CASE B+D+E) 359
13.2 PROCESS IDENTIFICATION WITH ADDITIONAL TEST SIGNALS 361 13.3
METHODS FOR IDENTIFICATION IN CLOSED LOOP 363
13.3.1 INDIRECT PROCESS IDENTIFICATION WITHOUT ADDITIONAL TEST SIGNALS
363
13.3.2 INDIRECT PROCESS IDENTIFICATION WITH ADDITIONAL TEST SIGNALS. 364
13.3.3 DIRECT PROCESS IDENTIFICATION WITHOUT ADDITIONAL TEST SIGNALS 364
13.3.4 DIRECT PROCESS IDENTIFICATION WITH ADDITIONAL TEST SIGNALS . 364
13.4 SUMMARY 365
PROBLEMS 365
REFERENCES 366
PART IV IDENTIFICATION WITH PARAMETRIC MODELS - CONTINUOUS TIME SIGNALS
14 PARAMETER ESTIMATION FOR FREQUENCY RESPONSES 369
14.1 INTRODUCTION 369
14.2 METHOD OF LEAST SQUARES FOR FREQUENCY RESPONSE APPROXIMATION
(FR-LS) 370
14.3 SUMMARY 374
PROBLEMS 376
REFERENCES 376
15 PARAMETER ESTIMATION FOR DIFFERENTIAL EQUATIONS AND CONTINUOUS TIME
PROCESSES 379
15.1 METHOD OF LEAST SQUARES 379
15.1.1 FUNDAMENTAL EQUATIONS 379
15.1.2 CONVERGENCE 382
15.2 DETERMINATION OF DERIVATIVES 383
15.2.1 NUMERICAL DIFFERENTIATION 383
15.2.2 STATE VARIABLE FILTERS 384
15.2.3 FIR FILTERS 391
15.3 CONSISTENT PARAMETER ESTIMATION METHODS 393
15.3.1 METHOD OF INSTRUMENTAL VARIABLES 393
15.3.2 EXTENDED KAIMAN FILTER, MAXIMUM LIKELIHOOD METHOD 395 15.3.3
CORRELATION AND LEAST SQUARES 395
15.3.4 CONVERSION OF DISCRETE-TIME MODELS 398
15.4 ESTIMATION OF PHYSICAL PARAMETERS 399
15.5 PARAMETER ESTIMATION FOR PARTIALLY KNOWN PARAMETERS 404 15.6
SUMMARY 405
PROBLEMS 406
IMAGE 7
CONTENTS XV
REFERENCES 406
16 SUBSPACE METHODS 409
16.1 PRELIMINARIES 409
16.2 SUBSPACE 413
16.3 SUBSPACE IDENTIFICATION 414
16.4 IDENTIFICATION FROM IMPULSE RESPONSE 418
16.5 SOME MODIFICATIONS TO THE ORIGINAL FORMULATIONS 419
16.6 APPLICATION TO CONTINUOUS TIME SYSTEMS 420
16.7 SUMMARY 423
PROBLEMS 423
REFERENCES 424
PART V IDENTIFICATION OF MULTI-VARIABLE SYSTEMS
17 PARAMETER ESTIMATION FOR MIMO SYSTEMS 429
1 7. 1 TRANSFER FUNCTION MODELS 429
17.1.1 MATRIX POLYNOMIAL REPRESENTATION 431
17.2 STATE SPACE MODELS 432
17.2.1 STATE SPACE FORM 432
17.2.2 INPUT/OUTPUT MODELS 438
17.3 IMPULSE RESPONSE MODELS, MARKOV PARAMETERS 439
17.4 SUBSEQUENT IDENTIFICATION 441
17.5 CORRELATION METHODS 441
17.5.1 DE-CONVOLUTION 441
17.5.2 TEST SIGNALS 442
17.6 PARAMETER ESTIMATION METHODS 443
17.6.1 METHOD OF LEAST SQUARES 446
17.6.2 CORRELATION ANALYSIS AND LEAST SQUARES 446
17.7 SUMMARY 447
PROBLEMS 449
REFERENCES 449
PART VI IDENTIFICATION OF NON-LINEAR SYSTEMS
18 PARAMETER ESTIMATION FOR NON-LINEAR SYSTEMS 453
18.1 DYNAMIC SYSTEMS WITH CONTINUOUSLY DIFFERENTIABLE NON-LINEARITIES
453 VOLTERRA SERIES 454
HAMMERSTEIN MODEL 455
WIENER MODEL 457
MODEL ACCORDING TO LACHMANN 458
PARAMETER ESTIMATION 458
18.2 DYNAMIC SYSTEMS WITH NON-CONTINUOUSLY DIFFERENTIABLE
NON-LINEARITIES 460
18. 18. 18. 18. 18.
.1 .2 .3
.4 .5
IMAGE 8
XVI CONTENTS
18.2.1 SYSTEMS WITH FRICTION 460
18.2.2 SYSTEMS WITH DEAD ZONE 464
18.3 SUMMARY 465
PROBLEMS 465
REFERENCES 466
19 ITERATIVE OPTIMIZATION 469
19.1 INTRODUCTION 469
19.2 NON-LINEAR OPTIMIZATION ALGORITHMS 471
19.3 ONE-DIMENSIONAL METHODS 473
19.4 MULTI-DIMENSIONAL OPTIMIZATION 476
19.4.1 ZEROTH ORDER OPTIMIZERS 477
19.4.2 FIRST ORDER OPTIMIZERS 478
19.4.3 SECOND ORDER OPTIMIZERS 480
19.5 CONSTRAINTS 484
19.5.1 SEQUENTIAL UNCONSTRAINED MINIMIZATION TECHNIQUE 484 19.6
PREDICTION ERROR METHODS USING ITERATIVE OPTIMIZATION 491 19.7
DETERMINATION OF GRADIENTS 494
19.8 MODEL UNCERTAINTY 495
19.9 SUMMARY 496
PROBLEMS 498
REFERENCES 499
20 NEURAL NETWORKS AND LOOKUP TABLES FOR IDENTIFICATION 501 20.1
ARTIFICIAL NEURAL NETWORKS FOR IDENTIFICATION 501
20. 20. 20.
20. 20. 20.
. 1 ARTIFICIAL NEURAL NETWORKS FOR STATIC SYSTEMS 502
.2 ARTIFICIAL NEURAL NETWORKS FOR DYNAMIC SYSTEMS 512 .3 SEMI-PHYSICAL
LOCAL LINEAR MODELS 514
.4 LOCAL AND GLOBAL PARAMETER ESTIMATION 518
.5 LOCAL LINEAR DYNAMIC MODELS 519
.6 LOCAL POLYNOMIAL MODELS WITH SUBSET SELECTION 524 20.2 LOOK-UP TABLES
FOR STATIC PROCESSES 530
20.3 SUMMARY 534
PROBLEMS 534
REFERENCES 535
21 STATE AND PARAMETER ESTIMATION BY KAIMAN FILTERING 539
21.1 THE DISCRETE KAIMAN FILTER 540
21.2 STEADY-STATE KAIMAN FILTER 545
21.3 KAIMAN FILTER FOR TIME-VARYING DISCRETE TIME SYSTEMS 546 21.4
EXTENDED KAIMAN FILTER 547
21.5 EXTENDED KAIMAN FILTER FOR PARAMETER ESTIMATION 548
21.6 CONTINUOUS-TIME MODELS 549
21.7 SUMMARY 549
PROBLEMS 550
IMAGE 9
CONTENTS XVII
REFERENCES 550
PART VII MLSCELLANEOUS ISSUES
22 NUMERICAL ASPECTS 555
22.1 CONDITION NUMBERS 555
22.2 FACTORIZATION METHODS FOR P 557
22.3 FACTORIZATION METHODS FOR P~ L 558
22.4 SUMMARY 562
PROBLEMS 562
REFERENCES 563
23 PRACTICAL ASPECTS OF PARAMETER ESTIMATION 565
23.1 CHOICE OF INPUT SIGNAL 565
23.2 CHOICE OF SAMPLE RATE 567
23.2.1 INTENDED APPLICATION 568
23.2.2 FIDELITY OF THE RESULTING MODEL 568
23.2.3 NUMERICAL PROBLEMS 569
23.3 DETERMINATION OF STRUCTURE PARAMETERS FOR LINEAR DYNAMIC MODELS.
569 23.3.1 DETERMINATION OF DEAD TIME 570
23.3.2 DETERMINATION OF MODEL ORDER 572
23.4 COMPARISON OF DIFFERENT PARAMETER ESTIMATION METHODS 577 23.4.1
INTRODUCTORY REMARKS 577
23.4.2 COMPARISON OF A PRIORI ASSUMPTIONS 579
23.4.3 SUMMARY OF THE METHODS GOVERNED IN THIS BOOK 581 23.5 PARAMETER
ESTIMATION FOR PROCESSES WITH INTEGRAL ACTION 586 23.6 DISTURBANCES AT
THE SYSTEM INPUT 588
23.7 ELIMINATION OF SPECIAL DISTURBANCES 590
23.7.1 DRIFTS AND HIGH FREQUENT NOISE 590
23.7.2 OUTLIERS 592
23.8 VALIDATION 595
23.9 SPECIAL DEVICES FOR PROCESS IDENTIFICATION 597
23.9.1 HARDWARE DEVICES 597
23.9.2 IDENTIFICATION WITH DIGITAL COMPUTERS 598
23.10 SUMMARY 598
PROBLEMS 599
REFERENCES 599
PART VIII APPLICATIONS
IMAGE 10
XVIII CONTENTS
24 APPLICATION EXAMPLES 605
24.1 ACTUATORS 605
24.1.1 BRUSHLESS DC ACTUATORS 606
24.1.2 ELECTROMAGNETIC AUTOMOTIVE THROTTLE VALVE ACTUATOR 612 24.1.3
HYDRAULIC ACTUATORS 617
24.2 MACHINERY 628
24.2.1 MACHINE TOOL 628
24.2.2 INDUSTRIAL ROBOT 633
24.2.3 CENTRIFUGAL PUMPS 636
24.2.4 HEAT EXCHANGERS 639
24.2.5 AIR CONDITIONING 644
24.2.6 ROTARY DRYER 645
24.2.7 ENGINE TESTSTAND 648
24.3 AUTOMOTIVE VEHICLES 651
24.3.1 ESTIMATION OF VEHICLE PARAMETERS 651
24.3.2 BRAKING SYSTEMS 655
24.3.3 AUTOMOTIVE SUSPENSION 663
24.3.4 TIRE PRESSURE 667
24.3.5 INTERNAI COMBUSTION ENGINES 674
24.4 SUMMARY 679
REFERENCES 680
PART IX APPENDIX
A MATHEMATICAL ASPECTS 685
A.L CONVERGENCE FOR RANDOM VARIABLES 685
A.2 PROPERTIES OF PARAMETER ESTIMATION METHODS 687
A.3 DERIVATIVES OF VECTORS AND MATRICES 688
A.4 MATRIX INVERSION LEMMA 689
REFERENCES 690
B EXPERIMENTAL SYSTEMS 691
B.L THREE-MASS OSCILLATOR 691
REFERENCES 696
INDEX 697 |
| any_adam_object | 1 |
| author | Isermann, Rolf 1938- Münchhof, Marco 1975- |
| author_GND | (DE-588)105902845 (DE-588)13207432X |
| author_facet | Isermann, Rolf 1938- Münchhof, Marco 1975- |
| author_role | aut aut |
| author_sort | Isermann, Rolf 1938- |
| author_variant | r i ri m m mm |
| building | Verbundindex |
| bvnumber | BV037202815 |
| classification_rvk | ZQ 5070 ZQ 5220 ZQ 5222 |
| classification_tum | MSR 625f |
| ctrlnum | (OCoLC)697813245 (DE-599)DNB1000031055 |
| dewey-full | 629.8312 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
| dewey-raw | 629.8312 |
| dewey-search | 629.8312 |
| dewey-sort | 3629.8312 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik Elektrotechnik / Elektronik / Nachrichtentechnik Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| format | Book |
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| id | DE-604.BV037202815 |
| illustrated | Illustrated |
| indexdate | 2024-07-20T10:57:31Z |
| institution | BVB |
| isbn | 9783540788782 9783642422676 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-021117015 |
| oclc_num | 697813245 |
| open_access_boolean | |
| owner | DE-29T DE-83 DE-92 DE-703 DE-634 DE-859 DE-91G DE-BY-TUM DE-91 DE-BY-TUM DE-M347 DE-1050 DE-1102 DE-384 DE-573 |
| owner_facet | DE-29T DE-83 DE-92 DE-703 DE-634 DE-859 DE-91G DE-BY-TUM DE-91 DE-BY-TUM DE-M347 DE-1050 DE-1102 DE-384 DE-573 |
| physical | XXV, 705 S. Ill., graph. Darst. |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | Springer |
| record_format | marc |
| spelling | Isermann, Rolf 1938- Verfasser (DE-588)105902845 aut Identification of dynamic systems an introduction with applications Rolf Isermann ; Marco Münchhof Berlin [u.a.] Springer 2011 XXV, 705 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Systemidentifikation (DE-588)4121753-6 gnd rswk-swf Nichtlineares dynamisches System (DE-588)4126142-2 gnd rswk-swf Lineares dynamisches System (DE-588)4167727-4 gnd rswk-swf Frequenzgang (DE-588)4155400-0 gnd rswk-swf Parameterschätzung (DE-588)4044614-1 gnd rswk-swf Lineares dynamisches System (DE-588)4167727-4 s Systemidentifikation (DE-588)4121753-6 s Parameterschätzung (DE-588)4044614-1 s Frequenzgang (DE-588)4155400-0 s DE-604 Nichtlineares dynamisches System (DE-588)4126142-2 s Münchhof, Marco 1975- Verfasser (DE-588)13207432X aut Erscheint auch als Online-Ausgabe 978-3-540-78879-9 X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3423491&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=021117015&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Isermann, Rolf 1938- Münchhof, Marco 1975- Identification of dynamic systems an introduction with applications Systemidentifikation (DE-588)4121753-6 gnd Nichtlineares dynamisches System (DE-588)4126142-2 gnd Lineares dynamisches System (DE-588)4167727-4 gnd Frequenzgang (DE-588)4155400-0 gnd Parameterschätzung (DE-588)4044614-1 gnd |
| subject_GND | (DE-588)4121753-6 (DE-588)4126142-2 (DE-588)4167727-4 (DE-588)4155400-0 (DE-588)4044614-1 |
| title | Identification of dynamic systems an introduction with applications |
| title_auth | Identification of dynamic systems an introduction with applications |
| title_exact_search | Identification of dynamic systems an introduction with applications |
| title_full | Identification of dynamic systems an introduction with applications Rolf Isermann ; Marco Münchhof |
| title_fullStr | Identification of dynamic systems an introduction with applications Rolf Isermann ; Marco Münchhof |
| title_full_unstemmed | Identification of dynamic systems an introduction with applications Rolf Isermann ; Marco Münchhof |
| title_short | Identification of dynamic systems |
| title_sort | identification of dynamic systems an introduction with applications |
| title_sub | an introduction with applications |
| topic | Systemidentifikation (DE-588)4121753-6 gnd Nichtlineares dynamisches System (DE-588)4126142-2 gnd Lineares dynamisches System (DE-588)4167727-4 gnd Frequenzgang (DE-588)4155400-0 gnd Parameterschätzung (DE-588)4044614-1 gnd |
| topic_facet | Systemidentifikation Nichtlineares dynamisches System Lineares dynamisches System Frequenzgang Parameterschätzung |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=3423491&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=021117015&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT isermannrolf identificationofdynamicsystemsanintroductionwithapplications AT munchhofmarco identificationofdynamicsystemsanintroductionwithapplications |