Intelligent observer and control design for nonlinear systems:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2000
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIII, 339 S. Ill., graph. Darst. |
| ISBN: | 3540636390 |
Internformat
MARC
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| 245 | 1 | 0 | |a Intelligent observer and control design for nonlinear systems |c Dierk Schröder (ed.) |
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Datensatz im Suchindex
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|---|---|
| adam_text | DIERK SCHRODER (ED.) INTELLIGENT OBSERVER AND CONTROL DESIGN FOR
NONLINEAR SYSTEMS WITH 178 FIGURES SPRINGER CONTENTS 1 INTRODUCTION *
CONTROL ASPECTS 1 DIERK SCHRODER 1.1 LINEAR PLANTS 4 1.2 LINEAR PLANTS
WITH UNCERTAIN PARAMETERS 5 1.3 LINEAR PLANTS AND NONLINEAR CONTROLLERS
8 1.4 NONLINEAR PLANTS 9 1.5 OUR CONCEPTIONS OF NONLINEAR CONTROL
STRATEGIES AND OBSERVATION 13 1.6 REFERENCES 15 2 MOTION CONTROL 19
DIERK SCHRODER 2.1 CONTROL OF ELECTROMECHANICAL SYSTEMS 19 2.1.1
INTRODUCTION 19 2.1.2 CASCADED CONTROL 20 2.1.3 STATE-SPACE CONTROL 27
2.1.3.1 PROPORTIONAL STATE-SPACE CONTROLLER 27 2.1.3.2 STATE-SPACE
CONTROL WITH INTEGRATING CONTRIBUTION 34 2.1.4 GENERALIZED
CONSIDERATIONS FOR ELECTROMECHANICAL SYSTEMS ... 40 2.2 ACTUATOR,
MECHANICAL SYSTEM AND PROCESS 46 2.3 OBJECTIVES OF THIS BOOK (EXAMPLE
MOTION CONTROL) 59 2.4 CONCLUSIONS 63 2.5 REFERENCES 64 VIII . CONTENTS
3 LEARNING IN CONTROL ENGINEERING 67 ULRICH LENZ 3.1 INTELLIGENT CONTROL
AS ARTIFICIAL INTELLIGENCE 67 3.2 ARTIFICIAL INTELLIGENCE REALIZED BY A
NON-BIOLOGIC STRUCTURE ... 68 3.3 BASIC STRUCTURES FOR CONTROL 69 3.3.1
OPEN-LOOP CONTROL 69 3.3.2 CLOSED-LOOP CONTROL 70 3.3.3 CONDITIONAL
FEEDBACK CONTROL STRUCTURE 71 3.4 SCOPES FOR INTELLIGENT CONTROL 72
3.4.1 METHODS OF INTELLIGENT CONTROL 73 3.4.2 APPLICATION OF LEARNING IN
CONTROL ENGINEERING 73 3.4.2.1 EXAMPLE: DIRECT AND INDIRECT APPROACH 74
3.5 REQUIREMENTS FOR ADAPTIVE METHODS 75 3.5.1 STABILITY 76 3.5.2
IMPROVING THE CONTROLLER S PERFORMANCE 78 3.5.3 EXPANDABLE KNOWLEDGE 78
3.6 CLASSIFICATION DUE TO SYSTEM S STRUCTURE OR RESTRICTIONS 78 3.7
REFERENCES 80 4 NONLINEAR FUNCTION APPROXIMATORS 83 MICHAEL BEUSCHEL 4.1
NONLINEAR FUNCTION APPROXIMATION 83 4.1.1 CONCEPTS OF FUNCTION
APPROXIMATION 84 4.1.2 BASIS FUNCTIONS FOR FUNCTION APPROXIMATION 85
4.1.3 UNIVERSAL AND CONVERGENT FUNCTION APPROXIMATION 86 4.2 NEURAL
NETWORKS AS FUNCTION APPROXIMATORS 88 4.2.1 RADIAL BASIS FUNCTION (RBF)
NETWORK 88 4.2.2 GENERAL REGRESSION NEURAL NETWORK (GRNN) 89 4.2.2.1
GRNN AT MULTIDIMENSIONAL INPUT SPACE 91 4.2.2.2 POLYNOMIAL ACTIVATION
(DANN) 92 4.2.2.3 RESTRICTED UPDATE AREA 92 4.2.3 OTHER NEURAL NETWORK
APPROACHES 93 4.3 NEURO-FUZZY SYSTEMS AS FUNCTION APPROXIMATORS 94
CONTENTS IX 4.3.1 PRINCIPLES OF NEURO-FUZZY SYSTEMS 94 4.3.2 NEURO-FUZZY
EXAMPLE: TUNING OF OUTPUT FUZZY SETS 96 4.4 EXAMPLE 98 4.5 CONCLUSION
101 4.6 REFERENCES 102 5 SYSTEMATIC INTELLIGENT OBSERVER DESIGN 105
ULRICH LENZ 5.1 DEFINITIONS: DYNAMIC SYSTEMS CONTAINING AN ISOLATED
NONLINEARITY 107 5.1.1 DYNAMIC SYSTEM WITH AN ISOLATED NONLINEARITY 108
5.1.2 APPROXIMATION OF A STATIC NONLINEARITY . . . 110 5.2 HYBRID
NOTATION OF SIGNALS IN THE TIME AND FREQUENCY DOMAIN 111 5.3 SYSTEMATIC
OBSERVER DESIGN ILL 5.3.1 CONDITIONS ILL 5.3.2 OBSERVER DESIGN FOR
IDENTIFICATION 113 5.3.2.1 OBSERVER APPROACH 113 5.3.2.2 DIMENSIONING
THE OBSERVER FEEDBACK MATRIX L 113 5.3.2.3 SPECIFICATION OF THE ERROR
TRANSFER FUNCTION H(S) 114 5.3.2.4 DERIVING A STABLE ADAPTATION LAW
USING KNOWN ERROR MODELS . 115 5.3.2.5 REFLECTIONS ON PARAMETER
CONVERGENCE 121 5.3.2.6 SIMPLIFYING THE OBSERVER DESIGN 124 5.4
INTELLIGENT OBSERVER DESIGN FOLLOWING THE LUENBERGER APPROACH 124 5.4.1
PREREQUISITES 124 5.4.2 SYSTEMATIC OBSERVER DESIGN 126 5.4.2.1 DERIVING
THE ERROR TRANSFER FUNCTION 126 5.4.2.2 ADAPTATION LAW 127 5.5 SUMMARY
131 5.6 REFERENCES 132 6 IDENTIFICATION OF SEPARABLE NONLINEAR IT IES
135 FRANZ HANGL 6.1 PLANTS WITH SEPARABLE NONLINEARITIES 135 6.2
NONLINEAR OBSERVER APPROACH 136 X CONTENTS 6.2.1 IDENTIFICATION WITH
ACCESSIBLE STATES 136 6.2.1.1 ADAPTIVE OBSERVER ACCORDING TO THE
LUENBERGER OBSERVER . . . 136 6.2.2 IDENTIFICATION OF NONLINEARITIES IN
PLANTS WITH UNKNOWN INTERNAL STATES 139 6.2.2.1 NEURAL OBSERVER APPROACH
139 6.2.3 THE ERROR DECOUPLING FILTER 141 6.2.3.1 THE ADAPTIVE LAW 143
6.3 IMPLEMENTATION OF A-PRIORI KNOWLEDGE 144 6.3.1 ADDITIVE A-PRIORI
KNOWLEDGE 145 6.3.2 MULTIPLICATIVE A-PRIORI KNOWLEDGE 146 6.4 REFERENCES
148 7 IDENTIFICATION AND COMPENSATION OF FRICTION 149 THOMAS FRENZ 7.1
INTRODUCTION 149 7.2 DESIGN OF HARDWARE 155 7.3 IMPLEMENTATION: LEARNING
OF FRICTION CHARACTERISTIC 157 7.4 APPLICATION: COMPENSATION OF FRICTION
INFLUENCE 160 7.5 CONCLUSION 163 7.6 REFERENCES 165 8 DETECTION AND
IDENTIFICATION OF BACKLASH 167 DIETER STROBL 8.1 INTRODUCTION 167 8.2
EXAMPLE SYSTEM FOR BACKLASH IDENTIFICATION 168 8.2.1 MODEL OF AN ELASTIC
TWO-MASS SYSTEM 168 8.2.2 IDENTIFIABILITY OF THE BACKLASH CHARACTERISTIC
169 8.2.3 STATE SPACE DESCRIPTION OF THE NONLINEAR SYSTEM 170 8.3
IDENTIFICATION OF BACKLASH 172 8.3.1 REPRESENTATION OF BACKLASH FOR THE
IDENTIFICATION WITH A NEURAL NETWORK 172 8.3.2 LOAD-SIDE BACKLASH
OBSERVER (LBO) 174 8.3.2.1 STATE SPACE REPRESENTATION * 174 CONTENTS XI
8.3.2.2 OBSERVER DESIGN AND ERROR MODEL 174 8.3.3 MOTOR-SIDE BACKLASH
OBSERVER (MBO) 178 8.3.3.1 STATE SPACE REPRESENTATION 178 8.3.3.2
OBSERVER DESIGN AND ERROR MODEL 179 8.4 SIMULATION EXAMPLES 180 8.5
EXPERIMENTAL VALIDATION 183 8.5.1 EXPERIMENTAL SET-UP AND PARAMETERS 183
8.5.2 RESULTS OF ONLINE BACKLASH IDENTIFICATION 184 8.6 CONCLUSION 187
8.7 REFERENCES 188 9 IDENTIFICATION OF ISOLATED NONLINEARITIES IN
ROLLING MILLS 189 STEPHAN STRAUB 9.1 INTRODUCTION 189 9.2 NEURAL
NETWORKS IN ROLLING MILLS 189 9.2.1 PLANT DESCRIPTION 189 9.2.2
COMPENSATION OF WINDER ECCENTRICITIES 191 9.2.3 IDENTIFICATION OF THE
ROLL BITE 198 9.3 EXPERIMENTAL RESULTS 204 9.3.1 PLANT DESCRIPTION 204
9.3.2 IDENTIFICATION RESULTS 207 9.3.3 COMPENSATION RESULTS 209 9.4
CONCLUSION 214 9.5 REFERENCES 215 10 INPUT-OUTPUT LINEARIZATION: AN
INTRODUCTION 217 KURT FISCHLE , 10.1 A USEFUL CANONICAL FORM FOR
NONLINEAR SYSTEMS 217 10.2 BASIC CONCEPT OF INPUT-OUTPUT LINEARIZATION
223 10.3 SIMPLIFIED IDEAL CONTROL LAW 228 10.4 SHORT SUMMARY 232 10.5
REFERENCES - 233 F XH CONTENTS 11 STABLE MODEL REFERENCE NEUROCONTROL
235 KURT FISCHLE 11.1 INTRODUCTION 235 11.2 DESCRIPTION OF THE CONCEPT
237 11.3 APPLICATION EXAMPLE: NONLINEAR SECOND-ORDER SYSTEM 240 11.3.1
SIMULATION RESULTS 240 11.3.2 EXPERIMENTAL RESULTS 244 11.4
MODIFICATIONS 247 11.4.1 MODIFICATION FOR PLANTS WITH CONTROL SATURATION
249 11.4.2 MODIFICATION FOR PLANTS WITH L G L NF ~ L H{X) / CONST 249
11.4.3 METHOD WITH DIFFERENTIATION OF Y 250 11.4.4 MODIFICATIONS FOR
REDUCTION OF THE LEARNING TIMES 250 11.5 SHORT SUMMARY 251 11.6
REFERENCES 253 12 DYNAMIC NEURAL NETWORK COMPOSITIONS 255 STEPHAN STRAUB
12.1 INTRODUCTION 255 12.2 CLASSIFICATION OF IDENTIFICATION METHODS 256
12.2.1 MOTIVATION 256 12.2.2 DIFFERENT NET STRUCTURES 257 12.2.3
NONLINEAR OBSERVER STRUCTURES AND DYNAMIC IDENTIFICATORS . . . 260 12.3
IDENTIFICATION OF SYSTEMS WITH UNKNOWN STRUCTURE USING A DY- NAMIC
IDENTIFICATOR 265 12.3.1 MOTIVATION AND THEORETICAL APPROACH 266 12.3.2
DESIGN OF A DYNAMIC IDENTIFICATOR 269 12.3.3 POSSIBLE CONTROL CONCEPTS
272 12.3.4 SIMULATION 1: EXAMPLE 274 12.3.5 SIMULATION 2: TWO-MASS
SYSTEM 275 12.3.6 SIMULATION 3: INVERSE CONTROL 278 12.4 CONCLUSION 280
12.5 REFERENCES - 281 CONTENTS XIII 13 FURTHER STRATEGIES FOR NONLINEAR
CONTROL WITH NEURAL NET- WORKS 283 MARTIN RAU, ANNE ANGERMANN 13.1
INTRODUCTION 283 13.2 COMPENSATION AND STATE-SPACE CONTROL STRATEGIES
FOR A CLASS OF NONLINEAR SYSTEMS 284 13.2.1 SYSTEMS WITH ISOLATED
NONLINEARITIES AND NONLINEAR OBSERVER . . 285 13.2.2 EXACT COMPENSATION
OF ISOLATED NONLINEARITIES 285 13.2.2.1 TRANSFER FUNCTION DESCRIPTION OF
THE NONLINEAR SYSTEM 286 13.2.2.2 COMPENSATION ALGORITHM 287 13.2.2.3
REALIZATION OF THE COMPENSATION FILTER K(S) 288 13.2.3 STATE-SPACE
CONTROL OF THE COMPENSATED SYSTEM 291 13.2.3.1 SIMULATION EXAMPLE 293
13.2.4 CONCLUSIONS 297 13.2.5 ALTERNATE COMPENSATION AND CONTROL DESIGN
297 13.3 NONLINEAR CONTROL WITH A CONTROLLABLE CANONICAL FORM 302 13.4
NONLINEAR CONTROL DESIGN WITH NEURAL NETWORKS AND NUMERICAL OPTIMIZATION
304 13.4.1 MODEL REFERENCE NEURO CONTROL FOR SYSTEMS WITH ISOLATED NON-
LINEARITY 305 13.4.2 CONSIDERATIONS ON NUMERICAL OPTIMIZATION IN
NONLINEAR CONTROL 307 13.5 TIME-OPTIMAL TENSION CONTROL OF CONTINUOUS
MOVING WEBS SYS- TEMS 308 13.5.1 INTRODUCTION 308 13.5.2 CONTROLLER
DESIGN 313 13.5.3 EXPERIMENTAL VALIDATION 321 13.5.4 CONCLUSION 323 13.6
REFERENCES 326 LIST OF FIGURES 336 INDEX 337
|
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| indexdate | 2024-07-09T18:34:00Z |
| institution | BVB |
| isbn | 3540636390 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-008710570 |
| oclc_num | 42649617 |
| open_access_boolean | |
| owner | DE-29T DE-703 DE-91 DE-BY-TUM DE-M347 DE-706 DE-92 |
| owner_facet | DE-29T DE-703 DE-91 DE-BY-TUM DE-M347 DE-706 DE-92 |
| physical | XIII, 339 S. Ill., graph. Darst. |
| publishDate | 2000 |
| publishDateSearch | 2000 |
| publishDateSort | 2000 |
| publisher | Springer |
| record_format | marc |
| spelling | Intelligent observer and control design for nonlinear systems Dierk Schröder (ed.) Berlin [u.a.] Springer 2000 XIII, 339 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Automatic control Nonlinear control theory System design Neuro-Fuzzy-System (DE-588)4560677-8 gnd rswk-swf Nichtlineares System (DE-588)4042110-7 gnd rswk-swf Lernendes System (DE-588)4120666-6 gnd rswk-swf Systemidentifikation (DE-588)4121753-6 gnd rswk-swf Reglerentwurf (DE-588)4177447-4 gnd rswk-swf Beobachter Kybernetik (DE-588)4139504-9 gnd rswk-swf Nichtlineare Regelung (DE-588)4132964-8 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Nichtlineare Regelung (DE-588)4132964-8 s DE-604 Nichtlineares System (DE-588)4042110-7 s Lernendes System (DE-588)4120666-6 s Neuro-Fuzzy-System (DE-588)4560677-8 s Systemidentifikation (DE-588)4121753-6 s Beobachter Kybernetik (DE-588)4139504-9 s Reglerentwurf (DE-588)4177447-4 s Schröder, Dierk 1950- Sonstige (DE-588)109788079 oth HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008710570&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Intelligent observer and control design for nonlinear systems Automatic control Nonlinear control theory System design Neuro-Fuzzy-System (DE-588)4560677-8 gnd Nichtlineares System (DE-588)4042110-7 gnd Lernendes System (DE-588)4120666-6 gnd Systemidentifikation (DE-588)4121753-6 gnd Reglerentwurf (DE-588)4177447-4 gnd Beobachter Kybernetik (DE-588)4139504-9 gnd Nichtlineare Regelung (DE-588)4132964-8 gnd |
| subject_GND | (DE-588)4560677-8 (DE-588)4042110-7 (DE-588)4120666-6 (DE-588)4121753-6 (DE-588)4177447-4 (DE-588)4139504-9 (DE-588)4132964-8 (DE-588)4143413-4 |
| title | Intelligent observer and control design for nonlinear systems |
| title_auth | Intelligent observer and control design for nonlinear systems |
| title_exact_search | Intelligent observer and control design for nonlinear systems |
| title_full | Intelligent observer and control design for nonlinear systems Dierk Schröder (ed.) |
| title_fullStr | Intelligent observer and control design for nonlinear systems Dierk Schröder (ed.) |
| title_full_unstemmed | Intelligent observer and control design for nonlinear systems Dierk Schröder (ed.) |
| title_short | Intelligent observer and control design for nonlinear systems |
| title_sort | intelligent observer and control design for nonlinear systems |
| topic | Automatic control Nonlinear control theory System design Neuro-Fuzzy-System (DE-588)4560677-8 gnd Nichtlineares System (DE-588)4042110-7 gnd Lernendes System (DE-588)4120666-6 gnd Systemidentifikation (DE-588)4121753-6 gnd Reglerentwurf (DE-588)4177447-4 gnd Beobachter Kybernetik (DE-588)4139504-9 gnd Nichtlineare Regelung (DE-588)4132964-8 gnd |
| topic_facet | Automatic control Nonlinear control theory System design Neuro-Fuzzy-System Nichtlineares System Lernendes System Systemidentifikation Reglerentwurf Beobachter Kybernetik Nichtlineare Regelung Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008710570&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT schroderdierk intelligentobserverandcontroldesignfornonlinearsystems |