Robust industrial control systems: optimal design approach for polynomial systems
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| Sprache: | English |
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Chichester
Wiley
2006
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| Beschreibung: | XXII, 676 S. graph. Darst. |
| ISBN: | 0470020733 9780470020739 |
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| 020 | |a 9780470020739 |9 978-0-470-02073-9 | ||
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| 100 | 1 | |a Grimble, Michael J. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Robust industrial control systems |b optimal design approach for polynomial systems |c Michael J. Grimble |
| 264 | 1 | |a Chichester |b Wiley |c 2006 | |
| 300 | |a XXII, 676 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 856 | 4 | 2 | |m GBV Datenaustausch |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018822311&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
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| adam_text | ROBUST INDUSTRIAL CONTROL SYSTEMS: OPTIMAL DESIGN APPROACH FOR
POLYNOMIAL SYSTEMS MICHAEL J. GRIMBLE UNIVERSITY OF STRATHCLYDE, UK JOHN
WILEY &. SONS, LTD CONTENTS PREFACE XIX ACKNOWLEDGEMENTS XXI 1
INTRODUCTION TO OPTIMAL AND ROBUST CONTROL 1 1.1 INTRODUCTION 1 1.1.1
OPTIMALITY, FEEDBACK AND ROBUSTNESS 2 1.1.2 HIGH-INTEGRITY AND
FAULT-TOLERANT CONTROL SYSTEMS 3 1.1.3 SELF-HEALING CONTROL SYSTEMS 4
1.1.4 FAULT MONITORING AND DETECTION 5 1.1.5 ADAPTIVE VERSUS ROBUST
CONTROL 5 1.1.6 ARTIFICIAL INTELLIGENCE, NEURAL NETWORKS AND FUZZY
CONTROL 5 1.1.7 DISCRETE-TIME SYSTEMS 7 1.2 THE H 2 AND H^ SPACES AND
NORMS 8 1.2.1 GRAPHICAL INTERPRETATION OF THE HOO NORM 9 1.2.2 TERMS
USED IN H^ ROBUST CONTROL SYSTEMS DESIGN 9 1.3 INTRODUCTION TO H^
CONTROL DESIGN 9 1.3.1 PROPERTIES OF//OO ROBUST CONTROL DESIGN 11 1.3.2
COMPARISON OF H^ AND H 2 ILQG CONTROLLERS 12 1.3.3 RELATIONSHIPS BETWEEN
CLASSICAL DESIGN AND H^ ROBUST CONTROL 13 1.3.4 H 2 AND H^ DESIGN AND
RELATIONSHIP TO PID CONTROL 13 1.3.5 //QO POLYNOMIAL SYSTEMS SYNTHESIS
THEORY 13 1.4 STATE-SPACE MODELLING AND SYNTHESIS THEORY 14 1.4.1
STATE-SPACE SOLUTION OF DISCRETE-TIME H^ CONTROL PROBLEM 14 1.4.2 //OO
CONTROL DESIGN OBJECTIVES 15 1.4.3 STATE-FEEDBACK CONTROL SOLUTION 15
1.4.4 STATE-FEEDBACK CONTROL PROBLEM: CROSS-PRODUCT COSTING CASE 18
1.4.5 STATE-SPACE SOLUTION OF DISCRETE-TIME H^ FILTERING PROBLEM 19
1.4.6 BOUNDED REAL LEMMA 21 1.4.7 OUTPUT FEEDBACK H^ CONTROL PROBLEM 24
1.5 INTRODUCTION TO H 2 OR LQG POLYNOMIAL SYNTHESIS 29 1.5.1 SYSTEM
DESCRIPTION 29 1.5.2 COST FUNCTION AND SOLUTION 31 1.5.3 MINIMISATION OF
THE PERFORMANCE CRITERION 31 VIII CONTENTS 1.5.4 SOLUTION OF THE
DIOPHANTINE EQUATIONS AND STABILITY 34 1.5.5 H2ILQG DESIGN EXAMPLES 35
1.6 BENCHMARKING 40 1.6.1 RESTRICTED STRUCTURE BENCHMARKING 41 1.6.2
RULES FOR BENCHMARK COST FUNCTION SELECTION 42 1.7 CONDITION MONITORING
44 1.8 COMBINING H 2 , #00 AN D L OPTIMAL CONTROL DESIGNS 45 1.9 LINEAR
MATRIX INEQUALITIES 46 1.10 CONCLUDING REMARKS 47 1.11 PROBLEMS 48 1.12
REFERENCES 51 2 SCALAR H 2 AND LQG OPTIMAL CONTROL 57 2.1 INTRODUCTION
57 2.1.1 INDUSTRIAL CONTROLLER STRUCTURES 58 2.1.2 THE 2V2-DOF STRUCTURE
59 2.1.3 RESTRICTED STRUCTURE CONTROL LAWS 60 2.2 STOCHASTIC SYSTEM
DESCRIPTION 60 2.2.1 IDEAL RESPONSE MODELS 62 2.2.2 SYSTEM EQUATIONS 62
2.2.3 COST FUNCTION WEIGHTING TERMS 63 2.3 DUAL-CRITERION
COST-MINIMISATION PROBLEM 64 2.3.1 SOLUTION OF THE DUAL-CRITERION
MINIMISATION PROBLEM 66 2.3.2 THEOREM SUMMARISING LQG CONTROLLER 71
2.3.3 REMARKS ON THE EQUATIONS AND SOLUTION 73 2.3.4 DESIGN GUIDELINES
76 2.3.5 CONTROLLER IMPLEMENTATION 77 2.3.6 LQG SHIP-STEERING AUTOPILOT
APPLICATION 78 2.4 LQG CONTROLLER WITH ROBUST WEIGHTING FUNCTION 82
2.4.1 YOULA PARAMETERISATION 82 2.4.2 COST FUNCTION WITH ROBUST
WEIGHTING FUNCTION 83 2.4.3 SOLUTION OF THE DUAL-CRITERION PROBLEM WITH
ROBUST WEIGHTING 84 2.4.4 SUMMARY OF H 2 ILQG SYNTHESIS PROBLEM WITH
ROBUST WEIGHTING 86 2.4.5 COMMENTS ON THE SOLUTION 88 2.5 INTRODUCTION
TO THE STANDARD SYSTEM MODEL 89 2.5.1 STANDARD SYSTEM MODEL 89 2.6 THE
STANDARD SYSTEM MODEL STRUCTURE 91 2.6.1 POLYNOMIAL SYSTEM MODELS 92
2.6.2 REFERENCE MODEL 93 2.6.3 COST FUNCTION SIGNALS TO BE WEIGHTED 94
2.7 GENERALISED H 2 OPTIMAL CONTROL: STANDARD SYSTEM MODEL 95 2.7.1
OPTIMAL CONTROL SOLUTION OF THE STANDARD SYSTEM MODEL PROBLEM 96
CONTENTS IX 2.7.2 SUMMARY OF H2ILQG CONTROLLER FOR STANDARD SYSTEM
RESULTS 102 2.7.3 REMARKS ON THE SOLUTION 104 2.8 CONCLUDING REMARKS 105
2.9 PROBLEMS 105 2.10 REFERENCES 109 //OO OPTIMAL CONTROL OF SCALAR
SYSTEMS 113 3.1 INTRODUCTION 113 3.1.1 LINKS BETWEEN LQG AND H X
SOLUTIONS 114 3.1.2 REFERENCE AND FEEDBACK CONTROLLER DESIGNS 115 3.2
SYSTEM DESCRIPTION 115 3.3 LEMMA LINKING H^ AND LQG CONTROL PROBLEMS 115
3.4 CALCULATION OF THE H^ OPTIMAL CONTROLLER 116 3.4.1 SIMPLE H X
CONTROLLER STRUCTURES AND CALCULATIONS 117 3.4.2 ZERO MEASUREMENT NOISE
CASE 117 3.4.3 SOLUTION FOR THE//OO OPTIMAL CONTROLLER 118 3.4.4
STABILITY ROBUSTNESS OF MIXED-SENSITIVITY H^ DESIGNS 121 3.4.5 ONE-BLOCK
H X CONTROL PROBLEMS 122 3.5 THE G#OO CONTROL PROBLEM 123 3.5.1 G//OO
COST FUNCTION DEFINITION 124 3.5.2 YOULA PARAMETERISED FORM OF THE GH^
CONTROLLER 126 3.5.3 CALCULATION OF THE GH^ CONTROLLER 128 3.6 STABILITY
ROBUSTNESS OF GH^ DESIGNS 136 3.6.1 STRUCTURE OF THE UNCERTAIN SYSTEM
136 3.6.2 RATIONAL UNCERTAINTY STRUCTURE 137 3.6.3 STABILITY LEMMA 139
3.6.4 INFIUENCE OF THE UNCERTAINTY MODEL 140 3.6.5 DESIGN PROCEDURE FOR
UNCERTAIN SYSTEMS 140 3.6.6 //OO SELF-TUNING CONTROLLER FOR SYSTEMS WITH
PARAMETRIC UNCERTAINTY 147 3.7 STANDARD SYSTEM AND COST FUNCTION
DESCRIPTION 147 3.8 CALCULATION OF H^ CONTROLLER FOR THE STANDARD SYSTEM
147 3.8.1 F-ITERATION METHOD OF SOLVING THE ROBUST WEIGHTING EQUATION
148 3.8.2 /7 2 /#OO TRADE-OFF 149 3.9 PROBABILISTIC SYSTEM DESCRIPTIONS
AND H^ CONTROL 150 3.9.1 UNCERTAIN SYSTEM MODEL 151 3.9.2 COST FUNCTION
DEFINITION 153 3.9.3 UNCERTAIN SYSTEM AND POLYNOMIAL EQUATION
REPRESENTATION 155 3.9.4 DISCUSSION OF PROBABILISTIC UNCERTAINTY
MODELLING AND CONTROL 158 3.10 CONCLUDING REMARKS 158 3.11 PROBLEMS 159
3.12 REFERENCES 163 CONTENTS MULTIVARIABLE H 2 /LQG OPTIMAL CONTROL 167
4.1 INTRODUCTION 167 4.1.1 MATRIX FRACTION DESCRIPTIONS 168 4.2
MULTIVARIABLE SYSTEM DESCRIPTION 168 4.2.1 MULTIVARIABLE SENSITIVITY
MATRICES AND SIGNAL SPECTRA 170 4.2.2 CHOICE OF NOISE AND COST FUNCTION
WEIGHTINGS 171 4.3 LQG OPTIMAL CONTROL PROBLEM AND SOLUTION 171 4.3.1
SOLUTION OF THE H 2 /LQG PROBLEM 172 4.3.2 SOLUTION OF THE DIOPHANTINE
EQUATIONS 175 4.4 YOULA PARAMETERISATION AND AUXILIARY PROBLEM 182 4.4.1
YOULA PARAMETERISATION FOR THE AUXILIARY PROBLEM 184 4.4.2 SUMMARY OF
MULTIVARIABLE PROBLEM RESULTS WITH ROBUST WEIGHTING 186 4.5 H 2 /LQG
OPTIMAL CONTROL PROBLEM: MEASUREMENT NOISE CASE 187 4.5.1 PREDICTIVE
OPTIMAL CONTROL 190 4.5.2 SIMO PREDICTIVE OPTIMAL CONTROL PROBLEM 190
4.5.3 PROBABILISTIC DESCRIPTION OF UNCERTAINTY 196 4.6 THE GLQG OPTIMAL
CONTROL PROBLEM 196 4.6.1 SOLUTION OF THE GLQG PROBLEM 197 4.6.2
MODIFIED GLQG COST FUNCTION AND YOULA PARAMETERISATION 199 4.7 DESIGN OF
AUTOMATIC VOLTAGE REGULATORS 200 4.8 PSEUDO-STATE MODELLING AND
SEPARATION PRINCIPLE 210 4.8.1 INTRODUCTION TO PSEUDO-STATE METHODS 210
4.8.2 PSEUDO-STATE DISCRETE-TIME PLANT MODEL 211 4.8.3 DISCRETE
PSEUDO-STATE FEEDBACK OPTIMAL CONTROL 215 4.8.4 SOLUTION OF THE
PSEUDO-STATE FEEDBACK CONTROL PROBLEM 217 4.8.5 DISCRETE PSEUDO-STATE
ESTIMATION PROBLEM 222 4.8.6 SOLUTION OF THE DISCRETE-TIME PSEUDO-STATE
ESTIMATION PROBLEM 224 4.8.7 OUTPUT FEEDBACK CONTROL PROBLEM AND
SEPARATION PRINCIPLE 230 4.8.8 COMPUTATIONAL EXAMPLE 235 4.8.9
PSEUDO-STATE APPROACH REMARKS 240 4.9 CONCLUDING REMARKS 240 4.10
PROBLEMS 4.11 REFERENCES 241 245 MULTIVARIABLE H^ OPTIMAL CONTROL 249
5.1 INTRODUCTION 249 5.1.1 SUBOPTIMAL H^ CONTROL PROBLEMS 250 5.2 #OO
MULTIVARIABLE CONTROLLERS 250 5.2.1 DERIVATION OF THE WEIGHTING FILTER W
A 251 5.2.2 ROBUST WEIGHTING EQUATION 252 5.2.3 CALCULATION OF THE H^
OPTIMAL CONTROLLER 253 5.2.4 SUPEROPTIMALITY IN HOO DESIGN 258 5.2.5
SINGLE-INPUT MULTI-OUTPUT SYSTEMS 259 XI 5.3 ONE-BLOCK AND GH^ OPTIMAL
CONTROL PROBLEMS 259 5.3.1 ONE-BLOCK NEHARI PROBLEMS 259 5.3.2
CATEGORIES OF NEHARI PROBLEM 260 5.3.3 CONSTRAINT ON THE CHOICE OF
WEIGHTS FOR SIMPLIFIED DESIGN 261 5.3.4 GH^ OPTIMAL CONTROL PROBLEM 262
5.3.5 FINAL REMARKS ON LQG EMBEDDING H^ SOLUTION 267 5.4 SUBOPTIMAL H^
MULTIVARIABLE CONTROLLERS 268 5.4.1 SYSTEM DESCRIPTION AND GAME PROBLEM
269 5.4.2 LINEAR FRACTIONAL TRANSFORMATION 271 5.4.3 SIGNALS AND BOUNDED
POWER PROPERTY 271 5.4.4 SYSTEM AND COST WEIGHTING FUNCTION DEFINITIONS
272 5.5 POLYNOMIAL SYSTEM FOR SUBOPTIMAL H^ CONTROL PROBLEM 273 5.5.1
J-SPECTRAL FACTORISATION 274 5.5.2 DIOPHANTINE EQUATIONS FOR CAUSAL AND
NONCAUSAL DECOMPOSITION 274 5.6 SOLUTION OF SUBOPTIMAL H^ STATE FEEDBACK
PROBLEM 275 5.6.1 DISCRETE-TIME GAME PROBLEM 275 5.6.2 RELATIONSHIP
BETWEEN THE GAME AND H^ PROBLEMS 276 5.6.3 STANDARD SYSTEM MODEL
EQUATIONS AND SENSITIVITY 277 5.6.4 COMPLETING-THE-SQUARES 277 5.6.5
COST INDEX TERMS 278 5.6.6 COST INTEGRAND SIMPLIFICATION 279 5.6.7
CONTOUR INTEGRAL SIMPLIFICATION 279 5.6.8 OPTIMAL CONTROL LAW
CALCULATION 280 5.6.9 EXPRESSION FOR H%JH 0 281 5.6.10 SADDLE-POINT
SOLUTION 282 5.6.11 EXPRESSION FOR THE MINIMUM COST 283 5.7 SUBOPTIMAL
H^ STATE-FEEDBACK CONTROL PROBLEM 284 5.7.1 REMARKS ON THE SOLUTION 285
5.8 RELATIONSHIP BETWEEN POLYNOMIAL AND STATE-SPACE RESULTS 287 5.8.1
J-SPECTRAL FACTORISATION USING RICCATI EQUATION 288 5.8.2 RELATIONSHIP
BETWEEN THE POLYNOMIAL AND STATE-SPACE EQUATIONS 290 5.9 SOLUTION OF
SUBOPTIMAL OUTPUT FEEDBACK CONTROL PROBLEM 291 5.9.1 FINAL REMARKS ON
THE SUBOPTIMAL H^ SOLUTION 291 5.10 PROBLEMS 292 5.11 REFERENCES 295
ROBUST CONTROL SYSTEMS DESIGN AND IMPLEMENTATION 299 6.1 INTRODUCTION
299 6.1.1 THE CONTROL DESIGN PROBLEM 300 6.1.2 JUSTIFICATION FOR H^
CONTROL DESIGN 302 6.1.3 DYNAMIC COST FUNCTION WEIGHTINGS 303 6.1.4
PROPERTIES OF SENSITIVITY FUNCTIONS FOR DISCRETE-TIME SYSTEMS 304 XII
CONTENTS 6.2 AVOIDING IMPRACTICAL H^ DESIGNS 306 6.2.1 EQUALISING H^
SOLUTIONS AND IMPLICATIONS FOR MULTIVARIABLE DESIGN 307 6.3 POLE-ZERO
CANCELLATION PROPERTIES OF LQG AND H^ DESIGNS 308 6.3.1 POLYNOMIAL
SYSTEMS APPROACH 308 6.3.2 H 2 /LQG OPTIMAL CONTROL PROBLEM 308 6.3.3 H
X OPTIMAL CONTROL PROBLEM 310 6.3.4 CANCELLATION OF MINIMUM-PHASE PLANT
ZEROS 311 6.3.5 CANCELLATION OF STABLE PLANT POLES 312 6.3.6 SENDZIMIR
STEEL ROLLING MILL RESULTS 314 6.4 SYSTEM POLE AND ZERO PROPERTIES 314
6.4.1 CONTROLLER POLES AND ZEROS DUE TO WEIGHTINGS 314 6.4.2 POLES OF
THE CLOSED-LOOP SYSTEM 315 6.5 INFLUENCE OF WEIGHTINGS ON FREQUENCY
RESPONSES 316 6.5.1 STABILITY CRITERION AND COST FUNCTION WEIGHTING
SELECTION 316 6.5.2 INFLUENCE OF THE CHOICE OF WEIGHTS ON THE
SENSITIVITY FUNCTIONS 317 6.5.3 USE OF CONSTANT COST WEIGHTINGS IN HOC
DESIGN 319 6.5.4 POOR ROBUSTNESS DUE TO UNREALISTIC WEIGHTINGS 320 6.6
LOOP SHAPING DESIGN FOR MULTIVARIABLE SYSTEMS 324 6.6.1 SINGULAR VALUE
APPROXIMATIONS 324 6.6.2 ROBUSTNESS AND LOOP SHAPING 326 6.6.3 STABILITY
AND PERFORMANCE BOUNDARIES 327 6.6.4 ROBUST DESIGN FOR SYSTEMS IN
STANDARD MODEL FORM 328 6.6.5 STRUCTURED SINGULAR VALUES 330 6.7
FORMALISED DESIGN PROCEDURES 331 6.7.1 STEPS IN A H^ DESIGN PROCEDURE
331 6.7.2 COST FUNCTION WEIGHTING SELECTION FOR SCALAR SYSTEMS 332 6.8
MUTIVARIABLE ROBUST CONTROL DESIGN PROBLEM 334 6.8.1 PROBLEMS IN
MULTIVARIABLE CONTROL 335 6.8.2 POLES AND ZEROS OF MULTIVARIABLE SYSTEMS
336 6.8.3 INTERACTION MEASURES 337 6.9 MULTIVARIABLE CONTROL OF
SUBMARINE DEPTH AND PITCH 337 6.9.1 SELECTION OF WEIGHTS IN
MULTIVARIABLE PROBLEMS 337 6.9.2 MULTIVARIABLE SUBMARINE MOTION CONTROL
338 6.9.3 MULTIVARIABLE SUBMARINE CONTROL DESIGN RESULTS 340 6.9.4 SPEED
OF RESPONSE AND INTERACTION 343 6.9.5 ORDER OF THE WEIGHTING TERMS 346
6.9.6 TWO-DEGREE-OF-FREEDOM SUBMARINE CONTROL 346 6.10 RESTRICTED
STRUCTURE AND MULTIPLE MODEL CONTROL 346 6.10.1 FEEDFORWARD AND FEEDBACK
POLYNOMIAL SYSTEM PLANT 347 6.10.2 H 2 ILQG RESTRICTED STRUCTURE OPTIMAL
CONTROL PROBLEM 350 6.10.3 NUMERICAL ALGORITHM FOR SINGLE- AND
MULTI-MODEL SYSTEMS 362 6.10.4 HOT STRIP FINISHING MILL TENSION CONTROL
370 6.10.5 BENEFITS OF MULTIPLE-MODEL APPROACH 379 6.10.6 RESTRICTED
STRUCTURE BENCHMARKING 379 CONTENTS XIU 6.11 CONCLUDING REMARKS 381 6.12
PROBLEMS 382 6.13 REFERENCES 384 7 H 2 FILTERING, SMOOTHING AND
PREDICTION 389 7.1 INTRODUCTION 389 7.1.1 STANDARD SIGNAL PROCESSING
MODEL 390 7.2 SIGNAL PROCESSING SYSTEM DESCRIPTION 390 7.2.1 SUMMARY OF
ESTIMATION PROBLEM ASSUMPTIONS 391 7.2.2 OPTIMAL ESTIMATOR
TRANSFER-FUNCTION 392 7.2.3 SYSTEM EQUATIONS 392 7.2.4 POLYNOMIAL MATRIX
DESCRIPTIONS 392 7.2.5 SPECTRAL FACTORISATION 393 7.3 THE STANDARD H 2
OPTIMAL ESTIMATION PROBLEM 393 7.3.1 #2 STANDARD SYSTEM MODEL ESTIMATION
PROBLEM SOLUTION 394 7.3.2 ESTIMATION ERROR POWER SPECTRUM: COMPLETION
OF SQUARES 394 7.3.3 WIENER FILTERING SOLUTION 395 7.3.4 INTRODUCTION OF
THE FIRST DIOPHANTINE EQUATION 396 7.3.5 OPTIMAL ESTIMATOR WHEN SIGNAL
MODEL STABLE 396 7.3.6 OPTIMAL ESTIMATOR WHEN SIGNAL MODEL CAN BE
UNSTABLE 399 7.3.7 OPTIMAL ESTIMATOR WHEN SIGNAL MODEL CAN BE UNSTABLE
404 7.4 SOLUTION OF FILTERING, SMOOTHING AND PREDICATION PROBLEMS 408
7.4.1 STATE ESTIMATION PROBLEM 408 7.4.2 OUTPUT FILTERING AND PREDICTION
409 7.4.3 DECONVOLUTION ESTIMATION 410 7.4.4 ROBUST WEIGHTING FUNCTION W
A 413 7.4.5 EXTENSIONS OF THE ESTIMATOR CAPABILITIES 414 7.5 STRIP
THICKNESS ESTIMATION FROM ROLL FORCE MEASUREMENTS 415 7.5.1 ROLLING MILL
MODEL 416 7.5.2 CONTINUOUS-TIME DYNAMIC MILL MODEL 416 7.6 STRIP
THICKNESS ESTIMATION USING FORCE MEASURMENTS 418 7.7 STRIP THICKNESS
ESTIMATION USING X-RAY GAUGE MEASUREMENTS 421 7.8 STRIP THICKNESS
ESTIMATION USING GAUGE MEASUREMENTS 422 7.9 TIME-VARYING AND
NONSTATIONARY FILTERING 426 7.9.1 LINEAR MULTICHANNEL ESTIMATION PROBLEM
428 7.9.2 OUTPUT ESTIMATION PROBLEM 431 7.9.3 RELATIONSHIP TO THE KAIMAN
FILTERING PROBLEM 435 7.10 CONCLUSIONS 440 7.11 PROBLEMS 441 7.12
REFERENCES 442 8 HCE FILTERING, SMOOTHING AND PREDICTION 445 8.1
INTRODUCTION 8.1.1 THE HOO FILTERING PROBLEM 445 446 XIV CONTENTS 8.1.2
SMOOTHING FILTERS 447 8.1.3 PROBABILISTIC REPRESENTATION OF UNCERTAINTY
FOR FILTERING PROBLEMS 448 8.2 SOLUTION OF H^ OPTIMAL ESTIMATION PROBLEM
448 8.2.1 RELATIONSHIP BETWEEN H2 AND H^ MINIMISATION PROBLEMS 448 8.2.2
SOLUTION STRATEGY AND WEIGHTINGS 449 8.2.3 DERIVATION OF THE WEIGHTING
FILTER W 450 8.2.4 ROBUSTNESS WEIGHTING DIOPHANTINE EQUATION 451 8.2.5
#OO OPTIMAL ESTIMATOR FOR THE GENERALISED SYSTEM MODEL 452 8.2.6
PROPERTIES OF THE OPTIMAL ESTIMATOR 453 8.3 HOA DECONVOLUTION FILTERING
PROBLEM 453 8.3.1 DECONVOLUTION SYSTEM DESCRIPTION 454 8.3.2 SOLUTION OF
THE HQO DECONVOLUTION ESTIMATION PROBLEM 455 8.4 SUBOPTIMAL H^
MULTI-CHANNEL FILTERS 457 8.4.1 DISCRETE-TIME SYSTEM AND SIGNAL SOURCE
DESCRIPTIONS 457 8.4.2 DUALITY AND THE GAME PROBLEM 459 8.4.3 RESULTS
FOR THE SUBOPTIMAL H^, FILTERING PROBLEM 460 8.4.4 REMARKS ON THE
SOLUTION 462 8.5 RELEVANCE OF H^ METHODS TO SIGNAL PROCESSING
APPLICATIONS 463 8.6 FINAL REMARKS ON THE SUBOPTIMAL H^ FILTERING
PROBLEM 463 8.7 PROBLEMS 464 8.8 REFERENCES 465 9 APPLICATIONS OF U-JLQG
OPTIMAL CONTROL 469 9.1 INTRODUCTION 469 9.2 WIND TURBINE POWER CONTROL
SYSTEMS 470 9.2.1 DEFINITION OF WIND TURBINE TRANSFER FUNCTIONS 472
9.2.2 WEIGHTING FUNCTION DEFINITIONS 474 9.2.3 NUMERICAL RESULTS FOR
WIND TURBINE EXAMPLE 476 9.2.4 WIND TURBINE FEEDBACK CONTROLLER
CANCELLATION PROPERTIES 481 9.2.5 ROLE OF THE IDEAL-RESPONSE MODELS IN
DESIGN 483 9.2.6 FIXED- AND VARIABLE-SPEED WIND TURBINES 484 9.2.7
COMPARISON OF WIND TURBINE CONTROLLERS 484 9.2.8 WIND TURBINE CONDITION
MONITORING 484 9.3 DESIGN OF AN H 2 FLIGHT CONTROL SYSTEM 485 9.3.1
SYSTEM MODELS 485 9.3.2 DESIGN REQUIREMENTS AND SPECIFICATION 487 9.3.3
FLIGHT CONTROL SYSTEM: TIME AND FREQUENCY RESPONSES 490 9.3.4 FLIGHT
CONTROL SYSTEM DESIGN INCLUDING FLEXIBLE MODES 494 9.3.5 LQG FLIGHT
CONTROL STUDY DESIGN RESULTS 495 9.3.6 CLASSICAL AND LQG CONTROLLER
DESIGN 497 9.4 THICKNESS CONTROL SYSTEMS DESIGN USING FORCE FEEDBACK 500
9.4.1 OPTIMAL CONTROL SOLUTION FOR THE GAUGE CONTROL PROBLEM 502 9.4.2
ROLLING MILL MODEL 502 9.4.3 CONTINUOUS-TIME MILL MODELS 502 CONTENTS XV
9.4.4 DEFINITION OF THE POLYNOMIAL MODELS FOR THE STANDARD SYSTEM 503
9.4.5 COST FUNCTION DEFINITION 504 9.4.6 BUR ECCENTRICITY PROBLEM
RESULTS 506 9.4.7 MISMATCHED ECCENTRICITY MODEL CONDITIONS 510 9.5
THICKNESS CONTROL USING GAUGE MEASUREMENT 510 9.5.1 TRANSPORT DELAY IN
THICKNESS MEASUREMENT 512 9.5.2 FEEDBACK SYSTEM MODELS IN POLYNOMIAL
FORM 516 9.5.3 CHOICE OF COST FUNCTION WEIGHTINGS FOR GAUGE FEEDBACK
CONTROL PROBLEM 516 9.5.4 DEGREE OF STABILITY 517 9.6 SHIP ROLL
STABILISATION 518 9.6.1 FIN CONTROL UNIT 519 9.6.2 SPEED ADAPTATION 520
9.6.3 MODELS FOR THE SHIP STABILISATION SYSTEM 521 9.6.4 WEIGHTING
SELECTION FOR LQG ROLL STABILISATION DESIGN 521 9.6.5 FREQUENCY
RESPONSES 522 9.6.6 ADVANTAGES OF THE OPTIMAL SYSTEM IN COMPARISON WITH
CLASSICAL METHODS 524 9.6.7 RUDDER-ROLL STABILISATION AND SHIP STEERING
525 9.7 CONCLUDING REMARKS 525 9.8 PROBLEMS 526 9.9 REFERENCES 526 10
INDUSTRIAL APPLICATIONS OF H^ OPTIMAL CONTROL 529 10.1 INTRODUCTION 529
10.1.1 APPLICATIONS WHERE H X ROBUST CONTROL DESIGN IS APPLICABLE 530
10.1.2 SAFETY CRITICAL CONTROL SYSTEMS 530 10.1.3 FLIGHT CONTROL SYSTEMS
530 10.2 //OO FLIGHT CONTROL SYSTEMS DESIGN 532 10.2.1 DESIGN
REQUIREMENTS AND SPECIFICATION 534 10.2.2 DEFINITION OF COST FUNCTION
WEIGHTINGS 534 10.2.3 GENERALISED LQG AN D H^ CONTROLLER TIME- AND
FREQUENCY-RESPONSES 535 10.2.4 INTRODUCING A MEASUREMENT NOISE MODEL 540
10.2.5 COMPARISON OF CONTROLLERS 543 10.3 //OO GAUGE CONTROL SYSTEM
DESIGN USING FORCE FEEDBACK 543 10.3.1 THICKNESS CONTROL SYSTEM
FREQUENCY- AND TIME-RESPONSES 546 10.3.2 MISMATCHED ECCENTRICITY MODEL
AND ROBUSTNESS 551 10.3.3 THICKNESS PROFILE CONTROL 552 10.4 SUBMARINE
DEPTH AND COURSE-KEEPING H^ DESIGN 554 10.4.1 FORCES AND MOMENTS 554
10.4.2 DEPTH CONTROL 555 10.4.3 SEA-STATE AND SEA CURRENT DISTURBANCES
556 10.4.4 SUBMARINE MOTION DYNAMICS 558 CONTENTS 10.4.5 SUBMARINE DEPTH
AND PITCH CONTROL DESIGN 561 10.4.6 SUBMARINE DEPTH-KEEPING CONTROLLERS
562 10.4.7 SUBMARINE MODEL RESPONSES 563 10.4.8 MODEL TUNING 568 10.4.9
SUMMARY OF THE OUTPUT AND INPUT DISTURBANCE MODELS 571 10.4.10 SUBMARINE
DEPTH AND PITCH CONTROL 572 10.4.11 SUMMARY OF THE SELECTED WEIGHTING
TERMS 573 10.4.12 SCALAR DESIGN AND RESPONSES: DEPTH CONTROL 574 10.4.13
SCALAR DESIGN AND RESPONSES: PITCH CONTROL 578 10.4.14 IMPROVING THE
SCALAR SYSTEM TIME-RESPONSES 580 10.5 //*O CONTROL OF REMOTELY OPERATED
UNDERWATER VEHICLES 580 10.5.1 DESIGN OF ROV CONTROLLERS 584 10.6 HOO
CONTROL OF SURFACE SHIPS 585 10.6.1 //OO FIN ROLL STABILISATION SYSTEM
DESIGN 585 10.6.2 Z/OO SHIP TRACK-KEEPING CONTROL 588 10.7 CONCLUDING
REMARKS 591 10.8 PROBLEMS 592 10.9 REFERENCES 593 11 TIME-VARYING AND
NONLINEAR CONTROL 595 11.1 INTRODUCTION 595 11.2 OPTIMAL CONTROL OF
TIME-VARYING LINEAR SYSTEMS 596 11.2.1 LINEAR TIME-VARYING AND ADJOINT
OPERATORS 597 11.2.2 THE QUADRATIC COST INDEX 598 11.2.3 SOLUTION OF THE
TIME-VARYING LINEAR QUADRATIC CONTROL PROBLEM 599 11.3 MODELLING AND
CONTROL OF NONLINEAR SYSTEMS 602 11.3.1 NONLINEAR SYSTEMS MODELLING 603
11.3.2 HARD NONLINEARITIES 604 11.3.3 TYPICAL SYSTEM STRUCTURES 605
11.3.4 FEEDBACK LINEARISATION 605 11.4 NLQG COMPENSATION AND CONTROL 607
11.4.1 NONLINEAR CONTROL EXAMPLE 608 11.4.2 POLYNOMIAL VERSIONS OF PLANT
TRANSFER-FUNCTION OPERATORS 609 11.4.3 USE OF TIME-VARYING COST FUNCTION
WEIGHTING 610 11.4.4 THE NLQG ALGORITHM AND PROPERTIES 611 11.5 NLQG
EXAMPLE WITH INPUT AND OUTPUT NONLINEARITIES 612 11.5.1 SYSTEM AND COST
FUNCTION DESCRIPTION 613 11.5.2 SIMULATION RESULTS 613 11.5.3
FREQUENCY-DOMAIN RESULTS 614 11.5.4 IMPROVING NLQG CONTROL USING FUTURE
CHANGE INFORMATION 620 11.6 NONLINEAR GENERALISED MINIMUM VARIANCE
CONTROL 622 11.6.1 NONLINEAR SYSTEM DESCRIPTION 623 11.6.2 NONLINEAR AND
LINEAR SUBSYSTEM MODELS 625 11.6.3 SIGNALS 627 CONTENTS XVII 11.7
NONLINEAR GENERALISED MINIMUM VARIANCE PROBLEM 627 11.7.1 SOLUTION OF
THE NONLINEAR FEEDBACK/FEEDFORWARD CONTROL PROBLEM 629 11.7.2 POLYNOMIAL
MODELS FOR THE FEEDBACK/FEEDFORWARD CONTROL PROBLEM 630 11.7.3
DIOPHANTINE EQUATIONS 630 11.7.4 OPTIMISATION 632 11.7.5 ALTERNATIVE
CONTROL SOLUTION AND STABILITY 634 11.7.6 CLOSED-LOOP SYSTEM STABILITY
636 11.7.7 SIMPLIFYING THE CONTROLLER 636 11.7.8 EFFECT OF BIAS OR
STEADY-STATE LEVELS 637 11.8 NONLINEAR GMV CONTROL PROBLEM 639 11.9
NONLINEAR SMITH PREDICTOR 644 11.9.1 WEIGHTING SELECTION BASED ON AN
EXISTING CONTROLLER 647 11.10 CONCLUDING REMARKS 648 11.11 REFERENCES
669 APPENDIX 1 NOTATION AND MATHEMATICAL PRELIMINARIES 653 NOTATION 653
PARTITIONS 654 INFIMUM AND SUPREMUM 654 AL.L VECTORS 654 AI.2 MATRICES
655 AI.2.1 MATRIX INVERSE RELATIONSHIPS 657 AI.2.2 MATRIX SINGULAR VALUE
RELATIONSHIPS 658 AI.2.3 MATRIX NORM RELATIONSHIPS 659 AI.3 POLYNOMIAL
MATRICES 661 AI.3.1 POLYNOMIAL EQUATIONS 662 AI.4 TRANSFER-FUNCTION
MATRICES 663 AI.4.1 ADJOINT, ALL-PASS AND INNER FUNCTIONS 664 AI.4.2
TRANSFER-FUNCTION MATRIX FOR THE STANDARD SYSTEM MODEL 665 AI.5 VECTOR
AND NORMED SPACES 665 AI.5.1 HARDY SPACES AND NORMS 667 AI.6 REFERENCES
669
|
| any_adam_object | 1 |
| author | Grimble, Michael J. |
| author_facet | Grimble, Michael J. |
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| bvnumber | BV024700837 |
| ctrlnum | (OCoLC)254211851 (DE-599)BVBBV024700837 |
| dewey-full | 670.427 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 670 - Manufacturing |
| dewey-raw | 670.427 |
| dewey-search | 670.427 |
| dewey-sort | 3670.427 |
| dewey-tens | 670 - Manufacturing |
| discipline | Werkstoffwissenschaften / Fertigungstechnik |
| format | Book |
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| id | DE-604.BV024700837 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T22:08:09Z |
| institution | BVB |
| isbn | 0470020733 9780470020739 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-018822311 |
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| physical | XXII, 676 S. graph. Darst. |
| publishDate | 2006 |
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| spelling | Grimble, Michael J. Verfasser aut Robust industrial control systems optimal design approach for polynomial systems Michael J. Grimble Chichester Wiley 2006 XXII, 676 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018822311&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Grimble, Michael J. Robust industrial control systems optimal design approach for polynomial systems |
| title | Robust industrial control systems optimal design approach for polynomial systems |
| title_auth | Robust industrial control systems optimal design approach for polynomial systems |
| title_exact_search | Robust industrial control systems optimal design approach for polynomial systems |
| title_full | Robust industrial control systems optimal design approach for polynomial systems Michael J. Grimble |
| title_fullStr | Robust industrial control systems optimal design approach for polynomial systems Michael J. Grimble |
| title_full_unstemmed | Robust industrial control systems optimal design approach for polynomial systems Michael J. Grimble |
| title_short | Robust industrial control systems |
| title_sort | robust industrial control systems optimal design approach for polynomial systems |
| title_sub | optimal design approach for polynomial systems |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018822311&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT grimblemichaelj robustindustrialcontrolsystemsoptimaldesignapproachforpolynomialsystems |