Control theory:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
London
Inst. of Electrical Engineers
2004
|
| Ausgabe: | 2. ed. |
| Schriftenreihe: | IEE control engineering series
64 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXI, 297 S. graph. Darst. |
| ISBN: | 0863413390 0863413323 |
Internformat
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| 245 | 1 | 0 | |a Control theory |c J. R. Leigh |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a London |b Inst. of Electrical Engineers |c 2004 | |
| 300 | |a XXI, 297 S. |b graph. Darst. | ||
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| 490 | 1 | |a IEE control engineering series |v 64 | |
| 650 | 4 | |a Commande automatique | |
| 650 | 4 | |a Commande, Théorie de la | |
| 650 | 7 | |a Regelungstechnik |2 swd | |
| 650 | 4 | |a Automatic control | |
| 650 | 4 | |a Control theory | |
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Datensatz im Suchindex
| _version_ | 1804132753913937920 |
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| adam_text | CONTROL THEORY SECOND EDITION JR LEIGH THE INSTITUTION OF ELECTRICAL
ENGINEERS CONTENTS INTRODUCTION TO THE SECOND EDITION XVII THE
STRUCTURE, CONTENT AND PURPOSE OF THE BOOK XIX 1 CONTROL CONCEPTS: A
NON-MATHEMATICAL INTRODUCTION 1 1.1 GENERAL SYSTEMS IDEAS 1 1.2 WHAT IS
CONTROL THEORY? - AN INITIAL DISCUSSION 3 1.3 WHAT IS AUTOMATIC CONTROL?
6 1.4 SOME EXAMPLES OF CONTROL SYSTEMS 8 2 CONTROL DESIGN IDEAS: A
NON-MATHEMATICAL TREATMENT 11 2.1 INITIAL DISCUSSION 11 2.2 QUESTION:
CAN THE BEST POSSIBLE CONTROL ACTIONS BE SYNTHESISED BY SOME MECHANISM?
12 2.3 REQUIREMENTS FOR AN AUTOMATIC CONTROL SYSTEM 12 2.4 AUTOMATIC
FEEDBACK CONTROL 14 2.5 DIAGRAMS ILLUSTRATING AND AMPLIFYING SOME OF THE
CONCEPTS DESCRIBED SO FAR AND SHOWING RELATIONSHIPS TO A SOFTWARE
ENGINEERING CONTEXT 14 3 SYNTHESIS OF AUTOMATIC FEEDBACK CONTROL LOOPS:
A MORE QUANTITATIVE VIEW 19 3.1 FEEDBACK LOOPS: FURTHER DISCUSSION 19
3.2 WHAT SORTS OF CONTROL LAWS ARE THERE? 21 3.3 HOW FEEDBACK CONTROL
WORKS - A PRACTICAL VIEW 22 3.4 GENERAL CONDITIONS FOR THE SUCCESS OF
FEEDBACK CONTROL STRATEGIES 27 3.5 ALTERNATIVES TO FEEDBACK CONTROL 28
VIII CONTENTS HOW THE LAPLACE TRANSFORM GREATLY SIMPLIFIES SYSTEM
REPRESENTATION AND MANIPULATION 29 4.1 LAPLACE TRANSFORM TECHNIQUES 29
4.2 DEFINITION OF THE LAPLACE TRANSFORM 29 4A CONVERGENCE OF THE
INTEGRAL THAT DEFINES THE LAPLACE TRANSFORM 30 4B PROBLEMS WITH 0~ AND
0+ 31 4.3 USE OF THE LAPLACE TRANSFORM IN CONTROL THEORY 31 4.4 THE
CONCEPT OF TRANSFER FUNCTION 32 4.5 SYSTEM SIMPLIFICATION THROUGH BLOCK
MANIPULATION 32 4.6 HOW A TRANSFER FUNCTION CAN BE OBTAINED FROM A
DIFFERENTIAL EQUATION 33 4.7 POLES AND ZEROS OF A TRANSFER FUNCTION 34
4.8 UNDERSTANDING SYSTEM BEHAVIOUR FROM A KNOWLEDGE OF POLE AND ZERO
LOCATIONS IN THE COMPLEX PLANE 34 4.9 POLE PLACEMENT: SYNTHESIS OF A
CONTROLLER TO PLACE THE CLOSED LOOP POLES IN DESIRABLE POSITIONS 38 4.10
MOVING THE POLES OF A CLOSED LOOP SYSTEM TO DESIRABLE LOCATIONS - THE
ROOT LOCUS TECHNIQUE 39 4.11 OBTAINING THE TRANSFER FUNCTION OF A
PROCESS FROM EITHER A FREQUENCY RESPONSE CURVE OR A TRANSIENT RESPONSE
CURVE 40 4C CONVOLUTION - WHAT IT IS 41 4.12 DETERMINATION OF TRANSFER
FUNCTIONS BY CROSS-CORRELATION 43 4D CALCULATION OF RESONANT FREQUENCIES
FROM THE POLE-ZERO DIAGRAM 43 4E DERIVATION OF A FORMULA FOR DAMPED
NATURAL FREQUENCY 4 5 4F THE ROOT LOCUS OF A SYSTEM WITH OPEN-LOOP POLES
AND ZEROS LOCATED AS IN FIGURE 4.19 WILL INCLUDE A CIRCLE CENTRED ON THE
ZERO 46 FREQUENCY RESPONSE METHODS 47 5.1 INTRODUCTION 47 5.2 DESIGN
USING FREQUENCY RESPONSE METHODS - INITIAL EXPLANATION 47 5.3 FREQUENCY
RESPONSE OF A LINEAR SYSTEM 48 5.4 THE BODE DIAGRAM 48 5.5 FREQUENCY
RESPONSE AND STABILITY: AN IMPORTANT IDEA 49 5.6 SIMPLE EXAMPLE OF THE
USE OF THE FOREGOING IDEA IN FEEDBACK LOOP DESIGN 50 5.7 PRACTICAL POINT
- THE NEED FOR STABILITY MARGINS 51 5.8 GENERAL IDEA OF CONTROL DESIGN
USING FREQUENCY RESPONSE METHODS 51 5.9 OBTAINING THE FREQUENCY RESPONSE
OF A SYSTEM EXPERIMENTALLY - A LIST OF DIFFICULTIES 52 CONTENTS IX 5.10
DESIGN BASED ON KNOWLEDGE OF THE RESPONSE OF A SYSTEM TO A UNIT STEP
INPUT 52 5.11 HOW FREQUENCY RESPONSE IS OBTAINED BY CALCULATION FROM A
DIFFERENTIAL EQUATION 53 5.12 FREQUENCY RESPONSE TESTING CAN GIVE A GOOD
ESTIMATE OF A SYSTEM S TRANSFER FUNCTION 55 5.13 FREQUENCY RESPONSE OF A
SECOND ORDER SYSTEM 56 5 A THE FREQUENCY RESPONSE OF A SYSTEM WITH POLES
AND/OR ZEROS NEAR TO THE IMAGINARY AXIS 58 5B SOME INTERESTING AND
USEFUL IDEAS THAT WERE ORIGINATED BY BODE 58 5.14 NYQUIST DIAGRAM AND
NICHOLS CHART 60 MATHEMATICAL MODELLING 61 6.1 APPROACHES TO
MATHEMATICAL MODELLING 61 6.2 METHODS FOR THE DEVELOPMENT OF
MATHEMATICAL MODELS 62 6.3 MODELLING A SYSTEM THAT EXISTS, BASED ON DATA
OBTAINED BY EXPERIMENTATION 62 6.4 CONSTRUCTION OF MODELS FROM
THEORETICAL CONSIDERATIONS 64 6.5 METHODS/APPROACHES/TECHNIQUES FOR
PARAMETER ESTIMATION 64 6.6 WHY MODELLING IS DIFFICULT * AN IMPORTANT
DISCUSSION 66 6.7 FIXING OF PARAMETERS 67 6.8 PARAMETER ESTIMATION 67
6.9 REGRESSION ANALYSIS 67 6.10 ANALYSIS OF RESIDUALS 68 6A DOUBT AND
CERTAINTY 68 6B ANTICIPATORY SYSTEMS 70 6C CHAOS 71 6D MATHEMATICAL
MODELLING - SOME PHILOSOPHICAL COMMENTS 73 6E A STILL RELEVANT
ILLUSTRATION OF THE DIFFICULTY OF MATHEMATICAL MODELLING: THE LONG MARCH
TOWARDS DEVELOPING A QUANTITATIVE UNDERSTANDING OF THE HUMBLE WATER
WHEEL, 1590*1841 , 76 6F A POSTSCRIPT ON THE EFFECTIVENESS OF THOUGHT
EXPERIMENTS 79 6G EXPERIMENTATION ON PLANTS TO ASSIST IN MODEL
DEVELOPMENT - THE TESTS THAT YOU NEED MAY NOT BE IN THE TEXTBOOK! 79
LIMITS TO PERFORMANCE 83 7.1 STABILITY - INITIAL DISCUSSION 83 7A,
STABILITY THEORY - A LONG TERM THREAD THAT BINDS 8 4 7.2 STABILITY FOR
CONTROL SYSTEMS - HOW IT IS QUANTIFIED 86 7B THE INGENIOUS METHOD
OFHURWITZ 88 7.3 LINEAR SYSTEM STABILITY TESTS 88 7.4 STABILITY MARGIN
88 7.5 STABILITY TESTS FOR NON-LINEAR SYSTEMS 89 X CONTENTS 7.6 LOCAL
AND GLOBAL STABILITY 90 7.7 LYAPUNOV S SECOND (DIRECT) METHOD FOR
STABILITY DETERMINATION 91 7C GEOMETRIC INTERPRETATION OF LYAPUNOV S
SECOND METHOD 92 7.8 WHAT SETS THE LIMITS ON THE CONTROL PERFORMANCE? 94
7.9 HOW ROBUST AGAINST CHANGES IN THE PROCESS IS A MODERATELY AMBITIOUS
CONTROL LOOP? 96 7.10 LIMITS AND CONSTRAINTS ON SYNTHESIS: SUMMARY OF
POINTS 98 7.11 SYSTEMS THAT ARE DIFFICULT TO CONTROL: UNSTABLE SYSTEMS
98 7D CANCELLATION OF AN UNSTABLE POLE BY A MATCHING ZERO IN THE
CONTROLLER 99 7E SHIFTING AN UNSTABLE POLE BY FEEDBACK 100 7.12 SYSTEMS
THAT ARE DIFFICULT TO CONTROL - NON-MINIMUM PHASE SYSTEMS 101 7.13 SOME
INTERESTING THEORETICAL LIMITATIONS ON PERFORMANCE 102 7.13.1
SENSITIVITY FUNCTIONS AND THEIR INTERRELATION 102 7F MOTIVATION FOR THE
NAME: NON-MINIMUM PHASE SYSTEMS 103 7.13.2 INTEGRAL CONSTRAINTS IN THE
TIME DOMAIN 104 7.13.3 DESIGN CONSTRAINTS CAUSED BY BODE S THEOREM 105
7G MAPPING OF COMPLEX FUNCTIONS - A FEW POINTS THAT UNDERLIE CLASSICAL
CONTROL THEORY 106 7H DERIVATIVES OF A COMPLEX FUNCTION G{S) 108 71
SINGULARITIES OF A COMPLEX FUNCTION G(S) 108 SOME PRACTICAL ASPECTS OF
CONTROL DESIGN, JUSTIFICATION AND IMPLEMENTATION 111 8.1 HOW EFFICIENT
IS IT TO CONTROL AN UNKNOWN PROCESS BY A CONTROLLER THAT CONSISTS ONLY
OF A HIGH GAIN OF VALUE C THAT IN THE LIMIT BECOMES A RELAY CONTROLLER?
ILL 8.2 AN OFF-THE-SHELF APPROACH TO THE CONTROL OF AN UNKNOWN PROCESS
113 8.2.1 THE THREE-TERM CONTROLLER 113 8.2.2 ILLUSTRATION OF THE VALUE
OF AN INTEGRAL TERM IN REMOVING ANY CONSTANT ERROR 113 8.2.3
ILLUSTRATION OF THE VALUE OF A DERIVATIVE TERM TO CONTROL THE DEGREE OF
DAMPING 114 8.2.4 HOW CAN THE THREE COEFFICIENTS OF A THREE-TERM
CONTROLLER BE CHOSEN QUICKLY IN PRACTICE 114 8A HOW TO LEARN SOMETHING
FROM THE FIRST PART OF A STEP RESPONSE 120 8B NEW YORK TO SAN FRANCISCO
TELEPHONY - AN EARLY ILLUSTRATION OF THE SPECTACULAR SUCCESS OF FEEDBACK
IN ACHIEVING HIGH-FIDELITY AMPLIFICATIONS OF SIGNALS 122 8.3 CONVERTING
A USER S REQUIREMENTS INTO A CONTROL SPECIFICATION 123 CONTENTS X I 8.4
METHODOLOGIES FOR DECIDING THE SCOPE AND ATTRIBUTES OF AUTOMATIC CONTROL
SCHEMES FOR INDUSTRIAL APPLICATION (METHODOLOGIES FOR ECONOMIC
JUSTIFICATION OF INVESTMENT IN AUTOMATION) 124 8.4.1 METHODOLOGIES AND
ILLUSTRATIONS 124 8.5 REFERENCES ON METHODOLOGIES FOR ECONOMIC
JUSTIFICATION OF INVESTMENT IN AUTOMATION 130 9 LINEARISATION 131 9.1
THE MOTIVATION FOR LINEARISATION 131 9.2 WHAT IS LINEARISATION? 131
9.2.1 AN INITIAL TRIVIAL EXAMPLE 131 9.2.2 COMMENTS 132 9.3
LINEARISATION ABOUT A NOMINAL TRAJECTORY: ILLUSTRATION 133 9.4 THE
DERIVATIVE AS BEST LINEAR APPROXIMATION 134 9 A THE INVERSE FUNCTION
THEOREM 135 9B THE CONCEPT OF TRANSVERSALITY 136 10 MULTIVARIABLE LINEAR
PROCESSES 137 10.1 TRANSFER FUNCTION REPRESENTATIONS 137 10.2 STATE
SPACE REPRESENTATIONS 138 10.3 DESIGN OF FEEDBACK CONTROL SYSTEMS 139
10.4 TIME SOLUTION OF THE STATE SPACE EQUATION 139 10A IT SEEMS
REMARKABLE THAT AN OSCILLATORY SOLUTION CAN BE GENERATED BY REPEATED
MULTIPLICATION BY A CONSTANT MATRIX (SEE FIGURE 10.2) 141 10.5 DISCRETE
AND CONTINUOUS TIME MODELS: A UNIFIED APPROACH 141 10B GENERATION OF A
CONTROL SEQUENCE 142 10.6 THE CONCEPT OF CONTROLLABILITY FOR
MULTIVARIABLE SYSTEMS 143 10C CONSERVATION OF DIMENSION UNDER LINEAR
TRANSFORMATIONS 14 3 11 DISCRETE TIME AND COMPUTER CONTROL 145 11.1
COMPUTERS AS SYSTEM COMPONENTS - DEVICES THAT CAN CHANGE THEIR STATE
ONLY AT DISCRETE TIMES 145 11A A SIMPLE AND INFORMATIVE LABORATORY
EXPERIMENT 146 11.2 DISCRETE TIME ALGORITHMS 147 11.3 APPROACHES TO
ALGORITHM DESIGN 148 1 IB A CLEVER MANIPULATION - HOW THE DIGITAL TO
ANALOGUE CONVERTOR (ZERO ORDER HOLD) IS TRANSFERRED FOR CALCULATION
PURPOSES TO BECOME PART OF THE PROCESS TO BE CONTROLLED 149 11C
TAKAHASHI S ALGORITHM 151 11.4 OVERVIEW: CONCLUDING COMMENTS, GUIDELINES
FOR ALGORITHM CHOICE AND SOME COMMENTS ON PROCEDURE 152 XII CONTENTS 1
ID SOME DIFFICULTIES IN MOVING FROM DIFFERENTIAL EQUATIONS TO
APPROXIMATING DIFFERENCE EQUATIONS 153 HE DISCRETISATION 153 1 IF A
SIMPLE MATTER OF QUADRATIC BEHAVIOUR 154 11G CONTINUOUS IS NOT THE LIMIT
OF DISCRETE AS T *** 0 156 11H NON-UNIQUENESS OF INVERSE Z TRANSFORMS
157 111 STABILITY IS NORMALLY CONSIDERED TO BE A PROPERTY OF A SYSTEM SO
THAT FOR ANY BOUNDED INPUT A STABLE SYSTEM SHOULD PRODUCE A BOUNDED
OUTPUT 157 12 STATE ESTIMATION: THE KALMAN FILTER AND PREDICTION 159
12.1 STATE ESTIMATION - WHAT IT ATTEMPTS TO DO 159 12.2 HOW A STATE
ESTIMATOR WORKS - THE KALMAN FILTER 160 12.3 THE KALMAN FILTER - MORE
DETAIL 160 12.4 OBTAINING THE OPTIMAL GAIN MATRIX 162 12.5 PREREQUISITES
FOR SUCCESSFUL APPLICATION OF THE KALMAN FILTER IN THE FORM SHOWN IN
FIGURE 12.4 163 12.6 DISCUSSION OF POINTS ARISING 163 12.7 PLANNING,
FORECASTING AND PREDICTION 164 12.7.1 APPROACHES TO PREDICTION 165
12.7.2 PHYSICALLY BASED MODELS FOR PREDICTION 166 12.8 PREDICTIVE
CONTROL 166 13 NON-LINEARITY 167 13.1 WHAT IS MEANT BY NON-LINEARITY 167
13.2 APPROACHES TO THE ANALYSIS OF NON-LINEAR SYSTEMS 169 13.3 THE
DESCRIBING FUNCTION METHOD FOR ANALYSIS OF CONTROL LOOPS CONTAINING
NON-LINEARITIES 170 13.4 LINEAR SECOND-ORDER SYSTEMS IN THE STATE PLANE
172 13.5 NON-LINEAR SECOND-ORDER SYSTEMS IN THE STATE PLANE 174 13.6
PROCESS NON-LINEARITY - LARGE SIGNAL PROBLEMS 176 13.7 PROCESS
NON-LINEARITY - SMALL SIGNAL PROBLEMS 176 14 OPTIMISATION 179 14.1
INITIAL DISCUSSION 179 14.2 OPTIMISATION - A FEW IDEAS THAT CAN FORM
BUILDING BLOCKS 179 14.2.1 DISCUSSION 185 14.3 TIME-OPTIMAL CONTROL 186
14A TIME-OPTIMAL CONTROL - A GEOMETRIC VIEW 188 14B THE FOLLOWING
GEOMETRIC ARGUMENT CONFORM A BASIS FOR THE DEVELOPMENT OF ALGORITHMS OR
FOR THE PROOF OF THE PONTRYAGIN MAXIMUM PRINCIPLE 191 14C CONSTRUCTION
OF TIME-OPTIMAL CONTROLS 192 CONTENTS XIII 15 DISTRIBUTED SYSTEMS 195
15.1 THE COSY IDEALISATION THAT A SYSTEM CAN BE CHARACTERISED BY ITS
BEHAVIOUR AT A POINT IN SPACE 195 15.2 ALTERNATIVE APPROACHES TO THE
MODELLING OF DISTRIBUTED SYSTEMS 196 15.2.1 THE REPRESENTATION OF A
SPATIAL REGION AS THE SUMMATION OF ELEMENTAL REGIONS 196 15.2.2 A
FOURIER TYPE APPROACH, IN WHICH AN ARBITRARY FUNCTION / ON AN INTERVAL
[0,1] IS APPROXIMATED BY A SUMMATION OF FUNCTIONS/; 197 15A WHEN CAN THE
BEHAVIOUR IN A REGION BE WELL APPROXIMATED AT A POINT? 198 15B
OSCILLATING AND OSCULATING APPROXIMATION OF CURVES 199 16 AN
INTRODUCTION TO ROBUST CONTROL DESIGN USING H^ METHODS 201 16.1
MOTIVATION 201 16.2 HARDY SPACES {H P , P 0 SPACES) AND THEIR
RELEVANCE TO CONTROL PROBLEMS 201 16.3 A SIMPLE VIEW OF H^ CONTROL LOOP
DESIGN 204 16.3.1 GUARANTEED STABILITY OF A FEEDBACK LOOP 204 16.3.2
ROBUST STABILITY OF A CLOSED LOOP 205 16.4 TOTAL INTERNAL STABILITY AND
DESIGN FOR DISTURBANCE REJECTION 206 16.4.1 SETTING THE SCENE 206 16.4.2
ROBUST STABILITY 207 16.4.3 DISTURBANCE REJECTION 208 16.5 SPECIFICATION
OF THE A G ENVELOPE 210 16.6 DERIVING H^ NORMS FROM DYNAMIC PROCESS
MODELS 211 16.6.1 SINGULAR VALUES AND EIGENVALUES 211 16.6.2 EIGENVALUES
OF A RECTANGULAR MATRIX A 212 16.6.3 SINGULAR VALUES AND THEIR RELATION
TO EIGENVALUES 213 16.6.4 RELATIONS BETWEEN FREQUENCY AND TIME DOMAINS
213 16.7 A PROMISING VISUALISABLE DESIGN TOOL THAT WORKS WITHIN THE HOO
FRAME: THE V GAP METRIC 214 16.7.1 INTRODUCTION 214 16.7.2 SIMPLE
ILLUSTRATION OF THE USE OF THE V GAP METRIC 215 16.7.3 MORE ABOUT THE
TWO METRICS S V AND BC,D 215 16.7.4 THE INSIGHT PROVIDED BY THE V GAP
METRIC 217 16.7.5 TAKING INTO ACCOUNT THE WEIGHTS SHOWN IN FIGURE 16.13
TO ALLOW LOOP SHAPING 218 16.7.6 A DISCUSSION ON THE TWO METRICS S V AND
BC,D 218 16.8 ADAPTIVITY VERSUS ROBUSTNESS 219 16A A HIERARCHY OF SPACES
220 16.9 REFERENCES ON H P SPACES AND ON HOO CONTROL 222 XIV CONTENTS 17
NEURAL NETWORKS, FUZZY LOGIC, GENETIC ALGORITHMS, LEARNING SYSTEMS,
INTELLIGENT SYSTEMS 225 17.1 INTRODUCTION 225 17.2 ARTIFICIAL NEURAL
NETWORKS (ANN) 226 17.2.1 MOTIVATION 226 17.2.2 A BASIC BUILDING BLOCK -
THE NEURON 227 17.2.3 SIMPLE PROPERTIES OF A NEURON DEMONSTRATED IN THE
TWO DIMENSIONAL REAL PLANE 227 17.2.4 MULTILAYER NETWORKS 229 17.2.5
NEURAL NETWORK TRAINING 230 17.2.6 NEURAL NETWORK ARCHITECTURES TO
REPRESENT DYNAMIC PROCESSES 231 17.2.7 USING NEURAL NET BASED
SELF-ORGANISING MAPS FOR DATA-REDUCTION ARID CLUSTERING 233 17.2.8
UPCOMING RIVALS TO NEURAL NETWORKS? - SUPPORT VECTOR MACHINES (SVMS) AND
ADAPTIVE LOGIC NETWORKS (ALNS) 234 17.2.9 NEURAL NETS - SUMMARY 234 17.3
FUZZY SET THEORY AND FUZZY LOGIC 235 17.3.1 INTRODUCTION AND MOTIVATION
235 17.3.2 SOME CHARACTERISTICS OF FUZZY LOGIC 237 17.3.3 REFERENCES:
EARLY PIONEERING WORK 238 17.4 GENETIC ALGORITHMS 238 17.4.1 BASIC IDEAS
238 17.4.2 ARTIFICIAL GENETIC ALGORITHMS 239 17.4.3 GENETIC ALGORITHMS
AS DESIGN TOOLS 240 17.4.4 GA SUMMARY 241 17.4.5 REFERENCES 242 17.4.6
RIVALS TO GAS? AUTONOMOUS AGENTS AND SWARMS 242 17.5 LEARNING SYSTEMS
(SYSTEMS THAT LEARN) WITH OR WITHOUT SUPERVISION 242 17.5.1 BASIC IDEAS
242 17.5.2 LEARNING VERSUS ADAPTIVITY 243 17.5.3 STRUCTURAL
CHARACTERISTICS OF AN ABSTRACT LEARNING SYSTEM 243 17.6 INTELLIGENT
SYSTEMS 244 17.6.1 THE PROPERTIES THAT AN INTELLIGENT SYSTEM OUGHT TO
POSSESS 244 17.6.2 SELECTED REFERENCES 246 17A THE IDEA OF A PROBING
CONTROLLER 246 18 REVIEW - THE DEVELOPMENT OF CONTROL THEORY AND THE
EMERGENCE OF ARTIFICIAL INTELLIGENCE (AI) TECHNIQUES 249 18.1 A RAPID
REVIEW OF HOW CONTROL THEORY DEVELOPED 249 CONTENTS XV 19 18.2 18.3 18.4
18.5 18.6 REFERT 19.1 19.2 19.3 19.4 19.5 19.6 19.7 19.8 19.9 19.10
19.11 19.12 19.13 19.14 19.15 19.16 19.17 19.18 19.19 19.20 19.21 19.22
19.23 19.24 19.25 19.26 THE EMERGENCE OF AI TECHNIQUES CONTROL
APPLICATIONS ARE NOW EMBEDDED WITHIN AN IT INFRASTRUCTURE SUMMARY HOW
INTELLIGENT ARE AI (ARTIFICIAL INTELLIGENCE) METHODS? WHAT IS
INTELLIGENT CONTROL? NCES AND FURTHER READING LIBRARY BOOKS OTHER
SOURCES MAINSTREAM CONTROL LITERATURE OLDER MAINSTREAM CONTROL BOOKS
METHODOLOGIES FOR ECONOMIC JUSTIFICATION OF INVESTMENT IN AUTOMATION
STATE ESTIMATION NON-LINEAR SYSTEMS OPTIMISATION DISTRIBUTED PARAMETER
SYSTEMS H P SPACES AND H^, (ROBUST) CONTROL NEURAL NETWORKS AND SUPPORT
VECTOR METHODS FUZZY LOGIC AND FUZZY CONTROL GENETIC ALGORITHMS, GENETIC
PROGRAMMING AND OTHER PARALLEL EVOLUTIONARY SEARCH METHODS INTELLIGENT
AND LEARNING SYSTEMS ADAPTIVE AND MODEL-BASED CONTROL STOCHASTIC ASPECTS
OF CONTROL SOME OTHER CONTROL TOPICS GENERAL MATHEMATICS REFERENCES
ORDINARY DIFFERENTIAL EQUATIONS DIFFERENTIAL TOPOLOGY/DIFFERENTIAL
GEOMETRY/DIFFERENTIAL ALGEBRA THEORY OF EQUATIONS OPERATOR THEORY AND
FUNCTIONAL ANALYSIS APPLIED TO LINEAR CONTROL BOOKS OF HISTORICAL
INTEREST MISCELLANY USEFUL TABLES ALPHABETICAL LIST OF REFERENCES AND
SUGGESTIONS FOR FURTHER READING 252 253 253 253 254 255 255 255 256 256
257 257 257 257 258 258 258 259 259 259 259 260 260 260 261 261 262 262
263 264 264 264 NOTATION 285 INDEX 289
|
| any_adam_object | 1 |
| author | Leigh, James R. |
| author_facet | Leigh, James R. |
| author_role | aut |
| author_sort | Leigh, James R. |
| author_variant | j r l jr jrl |
| building | Verbundindex |
| bvnumber | BV019333272 |
| callnumber-first | Q - Science |
| callnumber-label | QA402 |
| callnumber-raw | QA402.3 TJ213 |
| callnumber-search | QA402.3 TJ213 |
| callnumber-sort | QA 3402.3 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | SK 880 |
| ctrlnum | (OCoLC)53460840 (DE-599)BVBBV019333272 |
| dewey-full | 629.8/312 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
| dewey-raw | 629.8/312 |
| dewey-search | 629.8/312 |
| dewey-sort | 3629.8 3312 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Mathematik Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| edition | 2. ed. |
| format | Book |
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| id | DE-604.BV019333272 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T19:57:50Z |
| institution | BVB |
| isbn | 0863413390 0863413323 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-012798186 |
| oclc_num | 53460840 |
| open_access_boolean | |
| owner | DE-703 |
| owner_facet | DE-703 |
| physical | XXI, 297 S. graph. Darst. |
| publishDate | 2004 |
| publishDateSearch | 2004 |
| publishDateSort | 2004 |
| publisher | Inst. of Electrical Engineers |
| record_format | marc |
| series | IEE control engineering series |
| series2 | IEE control engineering series |
| spelling | Leigh, James R. Verfasser aut Control theory J. R. Leigh 2. ed. London Inst. of Electrical Engineers 2004 XXI, 297 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier IEE control engineering series 64 Commande automatique Commande, Théorie de la Regelungstechnik swd Automatic control Control theory Regelungstheorie (DE-588)4122327-5 gnd rswk-swf H-unendlich-Kontrolltheorie (DE-588)4488490-4 gnd rswk-swf Kontrolltheorie (DE-588)4032317-1 gnd rswk-swf H-unendlich-Kontrolltheorie (DE-588)4488490-4 s Kontrolltheorie (DE-588)4032317-1 s Regelungstheorie (DE-588)4122327-5 s DE-604 IEE control engineering series 64 (DE-604)BV001899902 64 HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012798186&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Leigh, James R. Control theory IEE control engineering series Commande automatique Commande, Théorie de la Regelungstechnik swd Automatic control Control theory Regelungstheorie (DE-588)4122327-5 gnd H-unendlich-Kontrolltheorie (DE-588)4488490-4 gnd Kontrolltheorie (DE-588)4032317-1 gnd |
| subject_GND | (DE-588)4122327-5 (DE-588)4488490-4 (DE-588)4032317-1 |
| title | Control theory |
| title_auth | Control theory |
| title_exact_search | Control theory |
| title_full | Control theory J. R. Leigh |
| title_fullStr | Control theory J. R. Leigh |
| title_full_unstemmed | Control theory J. R. Leigh |
| title_short | Control theory |
| title_sort | control theory |
| topic | Commande automatique Commande, Théorie de la Regelungstechnik swd Automatic control Control theory Regelungstheorie (DE-588)4122327-5 gnd H-unendlich-Kontrolltheorie (DE-588)4488490-4 gnd Kontrolltheorie (DE-588)4032317-1 gnd |
| topic_facet | Commande automatique Commande, Théorie de la Regelungstechnik Automatic control Control theory Regelungstheorie H-unendlich-Kontrolltheorie Kontrolltheorie |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=012798186&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV001899902 |
| work_keys_str_mv | AT leighjamesr controltheory |