Reinforced methods for dynamical system identification and adaptive control
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Aachen
Shaker Verlag
2017
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MARC
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| 245 | 1 | 0 | |a Reinforced methods for dynamical system identification and adaptive control |c Rimantas Pupeikis |
| 264 | 1 | |a Aachen |b Shaker Verlag |c 2017 | |
| 300 | |a xi, 178 Seiten |b Illustrationen, Diagramme |c 21 cm, 285 g | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
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| 653 | |a Fachhochschul-/Hochschulausbildung | ||
| 653 | |a adaptive control | ||
| 653 | |a algorithm | ||
| 653 | |a identification | ||
| 653 | |a methods | ||
| 653 | |a observations | ||
| 653 | |a system | ||
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| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |a Pupeikis, Rimantas |t Reinforced methods for dynamical system identification and adaptive control |d Aachen : Shaker, 2017 |h Online-Ressourcen, 190 Seiten, 83 Illustrationen |
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Datensatz im Suchindex
| _version_ | 1804178497272283136 |
|---|---|
| adam_text | CONTENTS
1 I N TR O D U C TIO N
.......................................................................................
1
REFERENCES.............................................................................................
13
2 M ODEL O RD ER R O B U ST ID E N TIF IC A TIO N
..........................................
17
2.1 STATEMENT OF THE
PROBLEM............................................................ 17
2.2 MODEL ORDER DETERMINATION BEFORE THE PARAMETRIC
IDENTIFICATION OF AN OBJECT
.......................................................... 19
2.3 PRESENCE OF LARGE OUTLIERS IN AN OUTPUT
..................................... 22
2.4 MODEL ORDER DETERMINATION AFTER THE PARAMETRIC IDENTIFICATION
OF AN
OBJECT...................................................................................
23
2.5 MODEL ORDER DETERMINATION IN THE PRESENCE OF LARGE AND
SMALL O U TLIE
RS...............................................................................
25
2.6 SIMULATION RE S U LTS
.......................................................................
26
2.7
CONCLUSIONS...................................................................................
30
REFERENCES.............................................................................................
30
3 O PEN-L OOP S YSTEM P A RA M E TRIC ID E N TIF IC A TIO N
.......................
33
3.1 STATEMENT OF THE
PROBLEM............................................................ 33
3.2 PARAMETER ESTIMATION IN THE ABSENCE OF OUTLIERS
.......................
33
3.3 PARAMETER ESTIMATION IN THE PRESENCE OF OUTLIERS
.....................
36
3.4 SIMULATION RE S U LTS
.......................................................................
39
3.5
CONCLUSIONS...................................................................................
42
REFERENCES.............................................................................................
43
4 R ECURSIVE P A RA M E TRIC IDENTIFICATION OF O PEN-LOOP SYSTEM 45
4.1 STATEMENT OF THE
PROBLEM............................................................ 45
4.2 PARAMETER ESTIMATION IN AN ABSENCE OF O U TLIERS
.......................
45
4.3 RECURSIVE ESTIMATORS WITH THE VARIOUS NOISE FILTERS
.................
50
4.4 IDENTIFICATION IN THE PRESENCE OF O U
TLIERS................................... 57
4.5 DISCRETE SQUARE ROOT M -ESTIM ATORS
............................................
60
4.6 COMMON FORM OF RECURSIVE
M-ESTIMATORS................................... 63
4.7 ADAPTIVE HUBER*S ^-FUNCTION
......................................................
65
4.8 OUTLIERS CORRECTION
.......................................................................
67
4.9 SIMULATION RE S U LTS
........................................................................
68
4.10
CONCLUSIONS...................................................................................
71
REFERENCES.............................................................................................
72
5 D IRECT P A RA M E TRIC AL ID ENTIFICATION OF CLOSED-LOOP SYSTEM 73
5.1 STATEMENT OF THE
PROBLEM............................................................ 73
5.2 DIRECT APPROACH
...........................................................................
74
5.3 DETERMINATION OF RLS EFFICIENCY IN THE SPACE OF PARAMETERS .. 76
5.4 SIMULATION
EXAMPLE......................................................................
77
5.5 SIMULATION EXAMPLE WITH TIME-VARYING PARAM ETERS
...................
81
5.6
CONCLUSIONS...................................................................................
85
REFERENCES.............................................................................................
89
6 T W O-STAGE P A RA M E TRIC AL ID ENTIFICATION OF CLOSED-LOOP
S Y S T E M
.................................................................................................
91
6.1 TWO-STAGE APPROACH
.................................................................... 91
6.2 NUMERICAL SIMULATION IN THE PRESENCE OF THE CORRELATED NOISE . 95
6.3 SIMULATION EXAMPLE IN THE PRESENCE OF OUTLIERS
.............................
100
6.4
CONCLUSIONS.....................................................................................
107
REFERENCES...............................................................................................109
7 IDENTIFICATION OF LTI SYSTEM S W ITH H ARD N ONLINEARITIES .. . I L L
7.1
INTRODUCTION...................................................................................
I L L
7.2 STATEMENT OF THE
PROBLEM.............................................................. I
L L
7.3 DATA REARRANGEMENT
......................................................................113
7.4 INTERNAL SIGNAL
EXTRACTION..............................................................
116
7.5 SIMULATION RE S U LTS
.........................................................................
119
7.6
CONCLUSIONS.....................................................................................
128
REFERENCES...............................................................................................133
8 SELF-TUNING M V C ONTROL OF LTI SYSTEM S FOLLOWED BY TH E
S A TU R A TIO N
.............................................................................................135
8.1
INTRODUCTION...................................................................................
135
8.2 STATEMENT OF THE
PROBLEM..............................................................
135
8.3 RECONSTRUCTION OF AN INTERMEDIATE SIGNAL
...................................
136
8.4 SIMULATION RE S U LTS
..........................................................................141
8.5
CONCLUSIONS.....................................................................................
146
REFERENCES...............................................................................................151
9 TRACKING O F N O N STATIO N ARY S YSTEM P A RA M E TE RS JO IN TLY
W ITH TH E T IM E D E LA Y
..........................................................................153
9.1
INTRODUCTION...................................................................................
153
9.2 STATEMENT OF THE
PROBLEM..............................................................
154
9.3 INITIAL CRITERION
...............................................................................
155
CONTENTS XI
9.4 CORRECTIVE
OPERATOR........................................................................156
9.5 DECORRELATION OF A N O ISE
................................................................157
9.6 METHOD OF CORRECTIVE OPERATORS
....................................................
157
9.7 THE EFFICIENCY OF L R S
....................................................................159
9.8 SIMULATION RE S U LTS
..........................................................................161
9.9
CONCLUSIONS.....................................................................................
172
REFERENCES...............................................................................................173
A M ISSING D ATA RESTORATION ALGORITHM
.........................................175
|
| any_adam_object | 1 |
| author | Pupeikis, Rimantas |
| author_GND | (DE-588)1113883944 |
| author_facet | Pupeikis, Rimantas |
| author_role | aut |
| author_sort | Pupeikis, Rimantas |
| author_variant | r p rp |
| building | Verbundindex |
| bvnumber | BV044925264 |
| classification_rvk | ZQ 5260 |
| ctrlnum | (OCoLC)1036364284 (DE-599)DNB1128918323 |
| dewey-full | 629.82 629.80151 629.836 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
| dewey-raw | 629.82 629.80151 629.836 |
| dewey-search | 629.82 629.80151 629.836 |
| dewey-sort | 3629.82 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Mathematik Elektrotechnik / Elektronik / Nachrichtentechnik Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| format | Book |
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| id | DE-604.BV044925264 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:04:55Z |
| institution | BVB |
| institution_GND | (DE-588)1064118135 |
| isbn | 9783844052183 3844052186 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030318449 |
| oclc_num | 1036364284 |
| open_access_boolean | |
| owner | DE-83 |
| owner_facet | DE-83 |
| physical | xi, 178 Seiten Illustrationen, Diagramme 21 cm, 285 g |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Shaker Verlag |
| record_format | marc |
| spelling | Pupeikis, Rimantas Verfasser (DE-588)1113883944 aut Reinforced methods for dynamical system identification and adaptive control Rimantas Pupeikis Aachen Shaker Verlag 2017 xi, 178 Seiten Illustrationen, Diagramme 21 cm, 285 g txt rdacontent n rdamedia nc rdacarrier Beobachter Kybernetik (DE-588)4139504-9 gnd rswk-swf Systemidentifikation (DE-588)4121753-6 gnd rswk-swf Methode der kleinsten Quadrate (DE-588)4038974-1 gnd rswk-swf Adaptivregelung (DE-588)4000457-0 gnd rswk-swf Signalregenerierung (DE-588)4181274-8 gnd rswk-swf Nichtlineares Phänomen (DE-588)4136065-5 gnd rswk-swf Geschlossenes System (DE-588)4238924-0 gnd rswk-swf Offenes System (DE-588)4043370-5 gnd rswk-swf Lineares zeitinvariantes System (DE-588)4213494-8 gnd rswk-swf Parameteridentifikation (DE-588)4210689-8 gnd rswk-swf Fachhochschul-/Hochschulausbildung adaptive control algorithm identification methods observations system Adaptivregelung (DE-588)4000457-0 s Lineares zeitinvariantes System (DE-588)4213494-8 s Offenes System (DE-588)4043370-5 s Geschlossenes System (DE-588)4238924-0 s Parameteridentifikation (DE-588)4210689-8 s Systemidentifikation (DE-588)4121753-6 s Methode der kleinsten Quadrate (DE-588)4038974-1 s Nichtlineares Phänomen (DE-588)4136065-5 s Signalregenerierung (DE-588)4181274-8 s Beobachter Kybernetik (DE-588)4139504-9 s DE-604 Shaker Verlag (DE-588)1064118135 pbl Erscheint auch als Online-Ausgabe Pupeikis, Rimantas Reinforced methods for dynamical system identification and adaptive control Aachen : Shaker, 2017 Online-Ressourcen, 190 Seiten, 83 Illustrationen B:DE-101 application/pdf http://d-nb.info/1128918323/04 Inhaltsverzeichnis DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030318449&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Pupeikis, Rimantas Reinforced methods for dynamical system identification and adaptive control Beobachter Kybernetik (DE-588)4139504-9 gnd Systemidentifikation (DE-588)4121753-6 gnd Methode der kleinsten Quadrate (DE-588)4038974-1 gnd Adaptivregelung (DE-588)4000457-0 gnd Signalregenerierung (DE-588)4181274-8 gnd Nichtlineares Phänomen (DE-588)4136065-5 gnd Geschlossenes System (DE-588)4238924-0 gnd Offenes System (DE-588)4043370-5 gnd Lineares zeitinvariantes System (DE-588)4213494-8 gnd Parameteridentifikation (DE-588)4210689-8 gnd |
| subject_GND | (DE-588)4139504-9 (DE-588)4121753-6 (DE-588)4038974-1 (DE-588)4000457-0 (DE-588)4181274-8 (DE-588)4136065-5 (DE-588)4238924-0 (DE-588)4043370-5 (DE-588)4213494-8 (DE-588)4210689-8 |
| title | Reinforced methods for dynamical system identification and adaptive control |
| title_auth | Reinforced methods for dynamical system identification and adaptive control |
| title_exact_search | Reinforced methods for dynamical system identification and adaptive control |
| title_full | Reinforced methods for dynamical system identification and adaptive control Rimantas Pupeikis |
| title_fullStr | Reinforced methods for dynamical system identification and adaptive control Rimantas Pupeikis |
| title_full_unstemmed | Reinforced methods for dynamical system identification and adaptive control Rimantas Pupeikis |
| title_short | Reinforced methods for dynamical system identification and adaptive control |
| title_sort | reinforced methods for dynamical system identification and adaptive control |
| topic | Beobachter Kybernetik (DE-588)4139504-9 gnd Systemidentifikation (DE-588)4121753-6 gnd Methode der kleinsten Quadrate (DE-588)4038974-1 gnd Adaptivregelung (DE-588)4000457-0 gnd Signalregenerierung (DE-588)4181274-8 gnd Nichtlineares Phänomen (DE-588)4136065-5 gnd Geschlossenes System (DE-588)4238924-0 gnd Offenes System (DE-588)4043370-5 gnd Lineares zeitinvariantes System (DE-588)4213494-8 gnd Parameteridentifikation (DE-588)4210689-8 gnd |
| topic_facet | Beobachter Kybernetik Systemidentifikation Methode der kleinsten Quadrate Adaptivregelung Signalregenerierung Nichtlineares Phänomen Geschlossenes System Offenes System Lineares zeitinvariantes System Parameteridentifikation |
| url | http://d-nb.info/1128918323/04 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=030318449&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT pupeikisrimantas reinforcedmethodsfordynamicalsystemidentificationandadaptivecontrol AT shakerverlag reinforcedmethodsfordynamicalsystemidentificationandadaptivecontrol |