Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: Design, Analysis and Matlab Simulation
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Heidelberg [u.a.]
Springer
2013
|
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | XV, 365 S. graph. Darst. 235 mm x 155 mm |
| ISBN: | 9783642348150 3642348157 |
Internformat
MARC
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| 100 | 1 | |a Liu, Jinkun |e Verfasser |4 aut | |
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| 264 | 1 | |a Heidelberg [u.a.] |b Springer |c 2013 | |
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Datensatz im Suchindex
| _version_ | 1809404279171055616 |
|---|---|
| adam_text |
IMAGE 1
CONTENTS
1 INTRODUCTION 1
1.1 NEURAL NETWORK CONTROL 1
1.1.1 W H Y NEURAL NETWORK CONTROL? 1
1.1.2 REVIEW O F NEURAL NETWORK CONTROL 2
1.1.3 REVIEW O F R B F ADAPTIVE CONTROL 3
1.2 REVIEW O F R B F NEURAL NETWORK 3
1.3 R B F ADAPTIVE CONTROL FOR R O B O T MANIPULATORS 4
1.4 S FUNCTION DESIGN FOR CONTROL SYSTEM 5
1.4.1 S FUNCTION INTRODUCTION 5
1.4.2 BASIC PARAMETERS IN S FUNCTION 5
1.4.3 EXAMPLES 6
1.5 A N EXAMPLE O F A SIMPLE ADAPTIVE CONTROL SYSTEM 7
1.5.1 SYSTEM DESCRIPTION 7
1.5.2 ADAPTIVE CONTROL L A W DESIGN 7
1.5.3 SIMULATION EXAMPLE 9
APPENDIX 11
REFERENCES 15
2 R B F NEURAL NETWORK DESIGN AND SIMULATION 19
2.1 R B F NEURAL NETWORK DESIGN AND SIMULATION 19
2.1.1 R B F ALGORITHM 19
2.1.2 R B F DESIGN EXAMPLE WITH MATLAB SIMULATION 2 0
2.2 R B F NEURAL NETWORK APPROXIMATION BASED ON GRADIENT DESCENT METHOD
2 2
2.2.1 R B F NEURAL NETWORK APPROXIMATION 2 2
2.2.2 SIMULATION EXAMPLE 2 4
2.3 EFFECT O F GAUSSIAN FUNCTION PARAMETERS ON R B F APPROXIMATION 2 5
2.4 EFFECT O F HIDDEN NETS N U M B E R ON R B F APPROXIMATION 2 8
VII
HTTP://D-NB.INFO/102687243X
IMAGE 2
VIII
CONTENTS
2.5 R B F NEURAL NETWORK TRAINING FOR SYSTEM MODELING 33
2.5.1 RBF NEURAL NETWORK TRAINING 33
2.5.2 SIMULATION EXAMPLE 3 4
2.6 R B F NEURAL NETWORK APPROXIMATION 3 6
APPENDIX 37
REFERENCES 5 3
3 R B F NEURAL NETWORK CONTROL BASED O N GRADIENT DESCENT ALGORITHM 55
3.1 SUPERVISORY CONTROL BASED ON R B F NEURAL NETWORK 55
3.1.1 R B F SUPERVISORY CONTROL 5 5
3.1.2 SIMULATION EXAMPLE 5 6
3.2 RBFNN-BASED MODEL REFERENCE ADAPTIVE CONTROL 5 8
3.2.1 CONTROLLER DESIGN 5 8
3.2.2 SIMULATION EXAMPLE 5 9
3.3 R B F SELF-ADJUST CONTROL 61
3.3.1 SYSTEM DESCRIPTION 61
3.3.2 R B F CONTROLLER DESIGN 61
3.3.3 SIMULATION EXAMPLE 6 3
APPENDIX 6 3
REFERENCES 6 9
4 ADAPTIVE R B F NEURAL NETWORK CONTROL 71
4.1 ADAPTIVE CONTROL B A S E D ON NEURAL APPROXIMATION 71
4.1.1 PROBLEM DESCRIPTION 71
4.1.2 ADAPTIVE R B F CONTROLLER DESIGN 7 2
4.1.3 SIMULATION EXAMPLES 7 5
4.2 ADAPTIVE CONTROL BASED ON NEURAL APPROXIMATION WITH U N K N O W N
PARAMETER 7 9
4.2.1 PROBLEM DESCRIPTION 7 9
4.2.2 ADAPTIVE CONTROLLER DESIGN 7 9
4.2.3 SIMULATION EXAMPLES 8 3
4.3 A DIRECT M E T H O D FOR ROBUST ADAPTIVE CONTROL BY R B F 83
4.3.1 SYSTEM DESCRIPTION 83
4.3.2 DESIRED FEEDBACK CONTROL AND FUNCTION APPROXIMATION 8 6
4.3.3 CONTROLLER DESIGN AND PERFORMANCE ANALYSIS 87
4.3.4 SIMULATION EXAMPLE 9 0
APPENDIX 9 2
REFERENCES 112
5 NEURAL NETWORK SLIDING M O D E CONTROL 113
5.1 TYPICAL SLIDING M O D E CONTROLLER DESIGN 114
5.2 SLIDING M O D E CONTROL BASED ON R B F FOR SECOND-ORDER SISO
NONLINEAR SYSTEM 116
5.2.1 PROBLEM DESCRIPTION 116
IMAGE 3
CONTENTS IX
5.2.2 SLIDING MODE CONTROL BASED ON R B F
FOR U N K N O W N / ( - ) 117
5.2.3 SIMULATION EXAMPLE 118
5.3 SLIDING M O D E CONTROL BASED ON R B F FOR U N K N O W N / ( * ) AND
G(-) 120
5.3.1 INTRODUCTION 120
5.3.2 SIMULATION EXAMPLE 122
APPENDIX 123
REFERENCES 132
6 ADAPTIVE R B F CONTROL BASED O N GLOBAL APPROXIMATION 133
6.1 ADAPTIVE CONTROL WITH R B F NEURAL NETWORK COMPENSATION FOR ROBOTIC
MANIPULATORS 134
6.1.1 PROBLEM DESCRIPTION 134
6.1.2 R B F APPROXIMATION 135
6.1.3 R B F CONTROLLER AND ADAPTIVE L A W DESIGN AND ANALYSIS 136
6.1.4 SIMULATION EXAMPLES 140
6.2 R B F NEURAL ROBOT CONTROLLER DESIGN WITH SLIDING MODE ROBUST TERM
144
6.2.1 PROBLEM DESCRIPTION 144
6.2.2 R B F APPROXIMATION 147
6.2.3 CONTROL LAW DESIGN AND STABILITY ANALYSIS 147
6.2.4 SIMULATION EXAMPLES 148
6.3 ROBUST CONTROL BASED ON R B F NEURAL NETWORK WITH HJI 153
6.3.1 FOUNDATION 153
6.3.2 CONTROLLER DESIGN AND ANALYSIS 153
6.3.3 SIMULATION EXAMPLES 156
APPENDIX 159
REFERENCES 191
7 ADAPTIVE ROBUST R B F CONTROL BASED O N LOCAL APPROXIMATION . . . 193
7.1 ROBUST CONTROL BASED ON NOMINAL MODEL FOR ROBOTIC MANIPULATORS 193
7.1.1 PROBLEM DESCRIPTION 193
7.1.2 CONTROLLER DESIGN 194
7.1.3 STABILITY ANALYSIS 195
7.1.4 SIMULATION EXAMPLE 196
7.2 ADAPTIVE R B F CONTROL BASED ON LOCAL MODEL APPROXIMATION FOR
ROBOTIC MANIPULATORS 197
7.2.1 PROBLEM DESCRIPTION 197
7.2.2 CONTROLLER DESIGN 199
7.2.3 STABILITY ANALYSIS 2 0 0
7.2.4 SIMULATION EXAMPLES 2 0 3
IMAGE 4
X
C O N T E N T S
7.3 ADAPTIVE NEURAL NETWORK CONTROL O F ROBOT MANIPULATORS
IN T A S K SPACE 205
7.3.1 COORDINATION TRANSFORMATION FROM T A S K SPACE TO JOINT SPACE 208
7.3.2 NEURAL NETWORK MODELING O F ROBOT MANIPULATORS 208
7.3.3 CONTROLLER DESIGN 2 1 0
7.3.4 SIMULATION EXAMPLES 2 1 3
APPENDIX 217
REFERENCES 2 4 9
8 BACKSTEPPING CONTROL WITH R B F 251
8.1 INTRODUCTION 251
8.2 BACKSTEPPING CONTROL FOR INVERTED PENDULUM 2 5 2
8.2.1 SYSTEM DESCRIPTION 253
8.2.2 CONTROLLER DESIGN 253
8.2.3 SIMULATION EXAMPLE 2 5 4
8.3 BACKSTEPPING CONTROL BASED ON R B F FOR INVERTED PENDULUM . . . .
255
8.3.1 SYSTEM DESCRIPTION 2 5 5
8.3.2 BACKSTEPPING CONTROLLER DESIGN 2 5 6
8.3.3 ADAPTIVE L A W DESIGN 2 5 7
8.3.4 SIMULATION EXAMPLE 2 5 9
8.4 BACKSTEPPING CONTROL FOR SINGLE-LINK FLEXIBLE JOINT ROBOT 2 6 0
8.4.1 SYSTEM DESCRIPTION 2 6 0
8.4.2 BACKSTEPPING CONTROLLER DESIGN 2 6 2
8.5 ADAPTIVE BACKSTEPPING CONTROL WITH R B F FOR SINGLE-LINK FLEXIBLE
JOINT ROBOT 2 6 5
8.5.1 BACKSTEPPING CONTROLLER DESIGN WITH FUNCTION ESTIMATION 265
8.5.2 BACKSTEPPING CONTROLLER DESIGN WITH R B F APPROXIMATION 2 6 9
8.5.3 SIMULATION EXAMPLES 2 7 2
APPENDIX 2 7 6
REFERENCES 2 9 1
9 DIGITAL R B F NEURAL NETWORK CONTROL 2 9 3
9.1 ADAPTIVE R U N G E - K U T T A - M E R S O N METHOD 2 9 3
9.1.1 INTRODUCTION 293
9.1.2 SIMULATION EXAMPLE 2 9 5
9.2 DIGITAL ADAPTIVE CONTROL FOR SISO SYSTEM 2 9 5
9.2.1 INTRODUCTION 2 9 5
9.2.2 SIMULATION EXAMPLE 297
9.3 DIGITAL ADAPTIVE R B F CONTROL FOR T W O - L I N K MANIPULATORS 298
9.3.1 INTRODUCTION 2 9 8
9.3.2 SIMULATION EXAMPLE 2 9 9
APPENDIX 2 9 9
REFERENCES 309
IMAGE 5
CONTENTS XI
10 DISCRETE NEURAL NETWORK CONTROL 311
10.1 INTRODUCTION 311
10.2 DIRECT R B F CONTROL FOR A CLASS O F DISCRETE-TIME NONLINEAR SYSTEM
312
10.2.1 SYSTEM DESCRIPTION 312
10.2.2 CONTROLLER DESIGN AND STABILITY ANALYSIS 312
10.2.3 SIMULATION EXAMPLES 316
10.3 ADAPTIVE R B F CONTROL FOR A CLASS O F DISCRETE-TIME NONLINEAR
SYSTEM 3 1 9
10.3.1 SYSTEM DESCRIPTION 3 1 9
10.3.2 TRADITIONAL CONTROLLER DESIGN 3 2 0
10.3.3 ADAPTIVE NEURAL NETWORK CONTROLLER DESIGN 3 2 0
10.3.4 STABILITY ANALYSIS 322
10.3.5 SIMULATION EXAMPLES 324
APPENDIX 329
REFERENCES 337
11 ADAPTIVE R B F OBSERVER DESIGN AND SLIDING M O D E CONTROL 339
11.1 ADAPTIVE R B F OBSERVER DESIGN 339
11.1.1 SYSTEM DESCRIPTION 339
11.1.2 ADAPTIVE R B F OBSERVER DESIGN AND ANALYSIS 340
11.1.3 SIMULATION EXAMPLES 343
11.2 SLIDING MODE CONTROL BASED ON R B F ADAPTIVE OBSERVER 347
11.2.1 SLIDING M O D E CONTROLLER DESIGN 347
11.2.2 SIMULATION EXAMPLE 3 4 9
APPENDIX 351
REFERENCES 3 6 2
INDEX 363 |
| any_adam_object | 1 |
| author | Liu, Jinkun |
| author_facet | Liu, Jinkun |
| author_role | aut |
| author_sort | Liu, Jinkun |
| author_variant | j l jl |
| building | Verbundindex |
| bvnumber | BV040897218 |
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| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
| dewey-raw | 629.8360285632 |
| dewey-search | 629.8360285632 |
| dewey-sort | 3629.8360285632 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Informatik Elektrotechnik / Elektronik / Nachrichtentechnik Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| format | Book |
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| indexdate | 2024-09-06T00:26:28Z |
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| isbn | 9783642348150 3642348157 |
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| spelling | Liu, Jinkun Verfasser aut Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Design, Analysis and Matlab Simulation Jinkun Liu Heidelberg [u.a.] Springer 2013 XV, 365 S. graph. Darst. 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier Mechanisches System (DE-588)4132811-5 gnd rswk-swf Computersimulation (DE-588)4148259-1 gnd rswk-swf Stabilität (DE-588)4056693-6 gnd rswk-swf Reglerentwurf (DE-588)4177447-4 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Radiale Basisfunktion (DE-588)4380647-8 gnd rswk-swf Adaptivregelung (DE-588)4000457-0 gnd rswk-swf Adaptivregelung (DE-588)4000457-0 s Neuronales Netz (DE-588)4226127-2 s Radiale Basisfunktion (DE-588)4380647-8 s Reglerentwurf (DE-588)4177447-4 s Mechanisches System (DE-588)4132811-5 s Stabilität (DE-588)4056693-6 s Computersimulation (DE-588)4148259-1 s DE-604 X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=4161804&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=025876762&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Liu, Jinkun Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Design, Analysis and Matlab Simulation Mechanisches System (DE-588)4132811-5 gnd Computersimulation (DE-588)4148259-1 gnd Stabilität (DE-588)4056693-6 gnd Reglerentwurf (DE-588)4177447-4 gnd Neuronales Netz (DE-588)4226127-2 gnd Radiale Basisfunktion (DE-588)4380647-8 gnd Adaptivregelung (DE-588)4000457-0 gnd |
| subject_GND | (DE-588)4132811-5 (DE-588)4148259-1 (DE-588)4056693-6 (DE-588)4177447-4 (DE-588)4226127-2 (DE-588)4380647-8 (DE-588)4000457-0 |
| title | Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Design, Analysis and Matlab Simulation |
| title_auth | Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Design, Analysis and Matlab Simulation |
| title_exact_search | Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Design, Analysis and Matlab Simulation |
| title_full | Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Design, Analysis and Matlab Simulation Jinkun Liu |
| title_fullStr | Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Design, Analysis and Matlab Simulation Jinkun Liu |
| title_full_unstemmed | Radial Basis Function (RBF) Neural Network Control for Mechanical Systems Design, Analysis and Matlab Simulation Jinkun Liu |
| title_short | Radial Basis Function (RBF) Neural Network Control for Mechanical Systems |
| title_sort | radial basis function rbf neural network control for mechanical systems design analysis and matlab simulation |
| title_sub | Design, Analysis and Matlab Simulation |
| topic | Mechanisches System (DE-588)4132811-5 gnd Computersimulation (DE-588)4148259-1 gnd Stabilität (DE-588)4056693-6 gnd Reglerentwurf (DE-588)4177447-4 gnd Neuronales Netz (DE-588)4226127-2 gnd Radiale Basisfunktion (DE-588)4380647-8 gnd Adaptivregelung (DE-588)4000457-0 gnd |
| topic_facet | Mechanisches System Computersimulation Stabilität Reglerentwurf Neuronales Netz Radiale Basisfunktion Adaptivregelung |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=4161804&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=025876762&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT liujinkun radialbasisfunctionrbfneuralnetworkcontrolformechanicalsystemsdesignanalysisandmatlabsimulation |