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Datensatz im Suchindex
| DE-BY-OTHR_katkey | 5870749 |
|---|---|
| DE-BY-TUM_katkey | 2250674 |
| _version_ | 1831257124099850240 |
| adam_text | Titel: Adaptive dynamic programming with applications in optimal control
Autor: Liu, Derong
Jahr: 2017
Contents
1 Overview of Adaptive Dynamic Programming................. 1
1.1 Introduction........................................ 1
1.2 Reinforcement Learning............................... 3
1.3 Adaptive Dynamic Programming........................ 7
1.3.1 Basic Forms of Adaptive Dynamic Programming..... 10
1.3.2 Iterative Adaptive Dynamic Programming........... 15
1.3.3 ADP for Continuous-Time Systems................ 18
1.3.4 Remarks.................................... 21
1.4 Related Books...................................... 22
1.5 About This Book.................................... 26
References............................................... 27
Part I Discrete-Time Systems
2 Value Iteration ADP for Discrete-Time Nonlinear Systems....... 37
2.1 Introduction........................................ 37
2.2 Optimal Control of Nonlinear Systems
Using General Value Iteration.......................... 38
2.2.1 Convergence Analysis.......................... 40
2.2.2 Neural Network Implementation.................. 48
2.2.3 Generalization to Optimal Tracking Control......... 52
2.2.4 Optimal Control of Systems
with Constrained Inputs......................... 56
2.2.5 Simulation Studies............................. 59
2.3 Iterative Ö-Adaptive Dynamic Programming Algorithm
for Nonlinear Systems................................ 67
2.3.1 Convergence Analysis.......................... 69
2.3.2 Optimality Analysis............................ 77
2.3.3 Summary of Iterative 0-ADP Algorithm............ 80
2.3.4 Simulation Studies............................. 83
xx Contents
2.4 Conclusions........................................ 87
References............................................... 87
3 Finite Approximation Error-Based Value Iteration ADP......... 91
3.1 Introduction........................................ 91
3.2 Iterative Ö-ADP Algorithm with Finite
Approximation Errors................................. 92
3.2.1 Properties of the Iterative ADP Algorithm
with Finite Approximation Errors................. 93
3.2.2 Neural Network Implementation.................. 100
3.2.3 Simulation Study.............................. 104
3.3 Numerical Iterative 6-Adaptive Dynamic Programming....... 107
3.3.1 Derivation of the Numerical Iterative Ö-ADP
Algorithm................................... 107
3.3.2 Properties of the Numerical Iterative Ö-ADP
Algorithm................................... Ill
3.3.3 Summary of the Numerical Iterative Ö-ADP
Algorithm................................... 120
3.3.4 Simulation Study.............................. 121
3.4 General Value Iteration ADP Algorithm with Finite
Approximation Errors................................. 125
3.4.1 Derivation and Properties of the GVI Algorithm
with Finite Approximation Errors................. 125
3.4.2 Designs of Convergence Criteria with Finite
Approximation Errors.......................... 133
3.4.3 Simulation Study.............................. 140
3.5 Conclusions........................................ 147
References............................................... 147
4 Policy Iteration for Optimal Control of Discrete-Time Nonlinear
Systems................................................. 151
4.1 Introduction........................................ 151
4.2 Policy Iteration Algorithm............................. 152
4.2.1 Derivation of Policy Iteration Algorithm............ 153
4.2.2 Properties of Policy Iteration Algorithm............ 154
4.2.3 Initial Admissible Control Law................... 160
4.2.4 Summary of Policy Iteration ADP Algorithm........ 162
4.3 Numerical Simulation and Analysis...................... 162
4.4 Conclusions........................................ 173
References............................................... 174
Contents xxi
5 Generalized Policy Iteration ADP for Discrete-Time Nonlinear
Systems................................................. 177
5.1 Introduction........................................ 177
5.2 Generalized Policy Iteration-Based Adaptive Dynamic
Programming Algorithm............................... 177
5.2.1 Derivation and Properties of the GPI Algorithm...... 179
5.2.2 GPI Algorithm and Relaxation of Initial Conditions ... 188
5.2.3 Simulation Studies............................. 192
5.3 Discrete-Time GPI with General Initial Value Functions...... 199
5.3.1 Derivation and Properties of the GPI Algorithm...... 199
5.3.2 Relaxations of the Convergence Criterion
and Summary of the GPI Algorithm............... 211
5.3.3 Simulation Studies............................. 215
5.4 Conclusions........................................ 221
References............................................... 221
6 Error Bounds of Adaptive Dynamic Programming Algorithms. ... 223
6.1 Introduction........................................ 223
6.2 Error Bounds of ADP Algorithms for Undiscounted Optimal
Control Problems.................................... 224
6.2.1 Problem Formulation........................... 224
6.2.2 Approximate Value Iteration..................... 226
6.2.3 Approximate Policy Iteration..................... 231
6.2.4 Approximate Optimistic Policy Iteration............ 237
6.2.5 Neural Network Implementation.................. 241
6.2.6 Simulation Study.............................. 243
6.3 Error Bounds of Q-Function for Discounted Optimal Control
Problems........................................... 247
6.3.1 Problem Formulation........................... 247
6.3.2 Policy Iteration Under Ideal Conditions............. 249
6.3.3 Error Bound for Approximate Policy Iteration........ 254
6.3.4 Neural Network Implementation.................. 257
6.3.5 Simulation Study.............................. 259
6.4 Conclusions........................................ 262
References............................................... 263
Part II Continuous-Time Systems
7 Online Optimal Control of Continuous-Time Affine Nonlinear
Systems................................................. 267
7.1 Introduction........................................ 267
7.2 Online Optimal Control of Partially Unknown Affine
Nonlinear Systems................................... 267
7.2.1 Identifier-Critic Architecture for Solving HJB
Equation.................................... 269
xxii Contents
7.2.2 Stability Analysis of Closed-Loop System........... 281
7.2.3 Simulation Study.............................. 286
7.3 Online Optimal Control of Affine Nonlinear Systems
with Constrained Inputs............................... 291
7.3.1 Solving HJB Equation via Critic Architecture........ 294
7.3.2 Stability Analysis of Closed-Loop System
with Constrained Inputs......................... 298
7.3.3 Simulation Study.............................. 302
7.4 Conclusions........................................ 305
References............................................... 306
8 Optimal Control of Unknown Continuous-Time Nonaffine
Nonlinear Systems........................................ 309
8.1 Introduction........................................ 309
8.2 Optimal Control of Unknown Nonaffine Nonlinear Systems
with Constrained Inputs............................... 310
8.2.1 Identifier Design via Dynamic Neural Networks...... 311
8.2.2 Actor-Critic Architecture
for Solving HJB Equation....................... 316
8.2.3 Stability Analysis of Closed-Loop System........... 318
8.2.4 Simulation Study.............................. 323
8.3 Optimal Output Regulation of Unknown Nonaffine Nonlinear
Systems........................................... 327
8.3.1 Neural Network Observer....................... 328
8.3.2 Observer-Based Optimal Control Scheme
Using Critic Network.......................... 333
8.3.3 Stability Analysis of Closed-Loop System........... 337
8.3.4 Simulation Study.............................. 340
8.4 Conclusions........................................ 343
References............................................... 343
9 Robust and Optimal Guaranteed Cost Control
of Continuous-Time Nonlinear Systems....................... 345
9.1 Introduction........................................ 345
9.2 Robust Control of Uncertain Nonlinear Systems............. 346
9.2.1 Equivalence Analysis and Problem Transformation.... 348
9.2.2 Online Algorithm and Neural Network
Implementation............................... 350
9.2.3 Stability Analysis of Closed-Loop System........... 353
9.2.4 Simulation Study.............................. 356
9.3 Optimal Guaranteed Cost Control of Uncertain Nonlinear
Systems........................................... 360
9.3.1 Optimal Guaranteed Cost Controller Design......... 362
9.3.2 Online Solution of Transformed Optimal Control
Problem..................................... 368
Contents xxiii
9.3.3 Stability Analysis of Closed-Loop System........... 373
9.3.4 Simulation Studies............................. 378
9.4 Conclusions........................................ 383
References............................................... 384
10 Decentralized Control of Continuous-Time Interconnected
Nonlinear Systems........................................ 387
10.1 Introduction........................................ 387
10.2 Decentralized Control of Interconnected Nonlinear Systems. ... 388
10.2.1 Decentralized Stabilization via Optimal Control
Approach.................................... 389
10.2.2 Optimal Controller Design of Isolated Subsystems .... 394
10.2.3 Generalization to Model-Free
Decentralized Control.......................... 400
10.2.4 Simulation Studies............................. 404
10.3 Conclusions........................................ 414
References............................................... 414
11 Learning Algorithms for Differential Games
of Continuous-Time Systems............................... 417
11.1 Introduction........................................ 417
11.2 Integral Policy Iteration for Two-Player Zero-Sum Games..... 418
11.2.1 Derivation of Integral Policy Iteration.............. 420
11.2.2 Convergence Analysis.......................... 423
11.2.3 Neural Network Implementation.................. 425
11.2.4 Simulation Studies............................. 428
11.3 Iterative Adaptive Dynamic Programming for Multi-player
Zero-Sum Games.................................... 431
11.3.1 Derivation of the Iterative ADP Algorithm.......... 433
11.3.2 Properties................................... 438
11.3.3 Neural Network Implementation.................. 444
11.3.4 Simulation Studies............................. 451
11.4 Synchronous Approximate Optimal Learning for Multi-player
Nonzero-Sum Games................................. 459
11.4.1 Derivation and Convergence Analysis.............. 460
11.4.2 Neural Network Implementation.................. 464
11.4.3 Simulation Study.............................. 473
11.5 Conclusions........................................ 478
References............................................... 478
xxiv Contents
Part III Applications
12 Adaptive Dynamic Programming for Optimal Residential Energy
Management............................................ 483
12.1 Introduction........................................ 483
12.2 A Self-learning Scheme for Residential Energy System
Control and Management.............................. 484
12.2.1 The ADHDP Method.......................... 488
12.2.2 A Self-learning Scheme for Residential Energy
System...................................... 489
12.2.3 Simulation Study.............................. 492
12.3 A Novel Dual Iterative Q-Learning Method for Optimal
Battery Management.................................. 496
12.3.1 Problem Formulation........................... 496
12.3.2 Dual Iterative Q-Learning Algorithm............... 497
12.3.3 Neural Network Implementation.................. 503
12.3.4 Numerical Analysis............................ 506
12.4 Multi-battery Optimal Coordination Control for Residential
Energy Systems..................................... 513
12.4.1 Distributed Iterative ADP Algorithm............... 515
12.4.2 Numerical Analysis............................ 527
12.5 Conclusions........................................ 533
References............................................... 533
13 Adaptive Dynamic Programming for Optimal Control of Coal
Gasification Process....................................... 537
13.1 Introduction........................................ 537
13.2 Data-Based Modeling and Properties..................... 538
13.2.1 Description of Coal Gasification Process
and Control Systems........................... 538
13.2.2 Data-Based Process Modeling and Properties........ 540
13.3 Design and Implementation of Optimal Tracking Control...... 546
13.3.1 Optimal Tracking Controller Design by Iterative ADP
Algorithm Under System and Iteration Errors........ 546
13.3.2 Neural Network Implementation.................. 554
13.4 Numerical Analysis................................... 557
13.5 Conclusions........................................ 568
References............................................... 569
14 Data-Based Neuro-Optimal Temperature Control
of Water Gas Shift Reaction................................ 571
14.1 Introduction........................................ 571
14.2 System Description and Data-Based Modeling.............. 572
14.2.1 Water Gas Shift Reaction....................... 572
14.2.2 Data-Based Modeling and Properties............... 573
Contents xxv
14.3 Design of Neuro-Optimal Temperature Controller........... 575
14.3.1 System Transformation......................... 575
14.3.2 Derivation of Stable Iterative ADP Algorithm........ 576
14.3.3 Properties of Stable Iterative ADP Algorithm
with Approximation Errors and Disturbances........ 578
14.4 Neural Network Implementation for the Optimal Tracking
Control Scheme..................................... 582
14.5 Numerical Analysis................................... 585
14.6 Conclusions........................................ 589
References............................................... 589
Index...................................................... 591
|
| any_adam_object | 1 |
| author | Liu, Derong Wei, Qinglai Wang, Ding Yang, Xiong Li, Hongliang |
| author_facet | Liu, Derong Wei, Qinglai Wang, Ding Yang, Xiong Li, Hongliang |
| author_role | aut aut aut aut aut |
| author_sort | Liu, Derong |
| author_variant | d l dl q w qw d w dw x y xy h l hl |
| building | Verbundindex |
| bvnumber | BV044023921 |
| classification_tum | ELT 000 MAS 000 |
| collection | ZDB-2-ENG |
| ctrlnum | (ZDB-2-ENG)978-3-319-50815-3 (OCoLC)971203691 (DE-599)BVBBV044023921 |
| dewey-full | 629.8 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
| dewey-raw | 629.8 |
| dewey-search | 629.8 |
| dewey-sort | 3629.8 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Maschinenbau / Maschinenwesen Elektrotechnik / Elektronik / Nachrichtentechnik Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| doi_str_mv | 10.1007/978-3-319-50815-3 |
| format | Electronic eBook |
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| id | DE-604.BV044023921 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T17:51:35Z |
| institution | BVB |
| isbn | 9783319508153 |
| issn | 2193-1577 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029431365 |
| oclc_num | 971203691 |
| open_access_boolean | |
| owner | DE-859 DE-860 DE-91 DE-BY-TUM DE-1046 DE-1043 DE-Aug4 DE-898 DE-BY-UBR DE-861 DE-573 DE-863 DE-BY-FWS DE-706 DE-634 DE-862 DE-BY-FWS DE-92 |
| owner_facet | DE-859 DE-860 DE-91 DE-BY-TUM DE-1046 DE-1043 DE-Aug4 DE-898 DE-BY-UBR DE-861 DE-573 DE-863 DE-BY-FWS DE-706 DE-634 DE-862 DE-BY-FWS DE-92 |
| physical | 1 Online-Ressource (xxx, 594 Seiten) Illustrationen |
| psigel | ZDB-2-ENG ZDB-2-ENG_2017 |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Springer |
| record_format | marc |
| series2 | Advances in industrial control |
| spellingShingle | Liu, Derong Wei, Qinglai Wang, Ding Yang, Xiong Li, Hongliang Adaptive dynamic programming with applications in optimal control Engineering Computational intelligence Control engineering Control Computational Intelligence Applications of Nonlinear Dynamics and Chaos Theory Ingenieurwissenschaften |
| title | Adaptive dynamic programming with applications in optimal control |
| title_auth | Adaptive dynamic programming with applications in optimal control |
| title_exact_search | Adaptive dynamic programming with applications in optimal control |
| title_full | Adaptive dynamic programming with applications in optimal control Derong Liu, Qinglai Wei, Ding Wang, Xiong Yang, Hongliang Li |
| title_fullStr | Adaptive dynamic programming with applications in optimal control Derong Liu, Qinglai Wei, Ding Wang, Xiong Yang, Hongliang Li |
| title_full_unstemmed | Adaptive dynamic programming with applications in optimal control Derong Liu, Qinglai Wei, Ding Wang, Xiong Yang, Hongliang Li |
| title_short | Adaptive dynamic programming with applications in optimal control |
| title_sort | adaptive dynamic programming with applications in optimal control |
| topic | Engineering Computational intelligence Control engineering Control Computational Intelligence Applications of Nonlinear Dynamics and Chaos Theory Ingenieurwissenschaften |
| topic_facet | Engineering Computational intelligence Control engineering Control Computational Intelligence Applications of Nonlinear Dynamics and Chaos Theory Ingenieurwissenschaften |
| url | https://doi.org/10.1007/978-3-319-50815-3 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029431365&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT liuderong adaptivedynamicprogrammingwithapplicationsinoptimalcontrol AT weiqinglai adaptivedynamicprogrammingwithapplicationsinoptimalcontrol AT wangding adaptivedynamicprogrammingwithapplicationsinoptimalcontrol AT yangxiong adaptivedynamicprogrammingwithapplicationsinoptimalcontrol AT lihongliang adaptivedynamicprogrammingwithapplicationsinoptimalcontrol |