mecha-Mechatronics concerns the synergistic and concurrent use of mechanics, electronics, computer engineering, and intelligent control systems in modeling, analyzing, design-ing, develo
Trang 2A Foundation Course
Trang 5CRC Press
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Trang 6“We live in a society exquisitely dependent on science and technology, in
which hardly anyone knows anything about science and technology.”
Carl Sagan
Trang 8Preface xxiii
Acknowledgments xxvii
Author xxix
1 Mechatronic Engineering 1
Study Objectives 1
1.1 Introduction 1
1.2 Mechatronic Systems 2
1.3 Modeling and Design 4
1.4 Mechatronic Design Concept 5
1.4.1 Coupled Design 6
1.4.2 Mechatronic Design Quotient 7
1.4.3 Design Evolution 8
1.5 Evolution of Mechatronics 9
1.6 Application Areas 10
1.7 Study of Mechatronics 11
1.8 Organization of the Book 12
Problems 14
Further Reading 15
2 Basic Elements and Components 17
Study Objectives 17
2.1 Introduction 17
2.2 Mechanical Elements 18
2.2.1 Mass (Inertia) Element 18
2.2.2 Spring (Stiffness) Element 20
2.2.3 Damping (Dissipation) Element 21
2.3 Fluid Elements 21
2.3.1 Fluid Capacitor or Accumulator (A-Type Element) 22
2.3.2 Fluid Inertor (T-Type Element) 22
2.3.3 Fluid Resistor (D-Type Element) 22
2.3.4 Derivation of Constitutive Equations 22
2.3.4.1 Fluid Capacitor 23
2.3.4.2 Fluid Inertor 26
2.3.4.3 Fluid Resistor 27
2.4 Thermal Elements 27
2.4.1 Thermal Capacitor 28
2.4.2 Thermal Resistor 28
2.4.2.1 Conduction 29
2.4.2.2 Convection 30
2.4.2.3 Radiation 30
Trang 92.4.3 Three-Dimensional Conduction 31
2.4.4 Biot Number 32
2.5 Mechanical Components 32
2.5.1 Transmission Components 33
2.5.2 Lead Screw and Nut 35
2.5.3 Harmonic Drives 38
2.6 Passive Electrical Elements and Materials 43
2.6.1 Resistor (Dissipation) Element 43
2.6.1.1 Conductance and Resistance 44
2.6.1.2 Resistivity 44
2.6.1.3 Effect of Temperature on Resistance 45
2.6.1.4 Effect of Strain on Resistance 46
2.6.1.5 Superconductivity 47
2.6.1.6 Color Code for Fixed Resistors 48
2.6.2 Dielectric Material and Capacitor Element 49
2.6.2.1 Permittivity 51
2.6.2.2 Capacitor Types 52
2.6.2.3 Color Code for Fixed Capacitors 52
2.6.2.4 Piezoelectricity 52
2.6.3 Magnetic Material and Inductor Element 55
2.6.3.1 Magnetism and Permeability 55
2.6.3.2 Hysteresis Loop 55
2.6.3.3 Magnetic Materials 55
2.6.3.4 Piezomagnetism 57
2.6.3.5 Hall-Effect Sensors 57
2.6.3.6 Magnetic Bubble Memories 58
2.6.3.7 Reluctance 58
2.6.3.8 Inductance 59
2.7 Active Electronic Components 60
2.7.1 Diodes 60
2.7.1.1 PN Junctions 60
2.7.1.2 Semiconductors 60
2.7.1.3 Depletion Region 61
2.7.1.4 Biasing 61
2.7.1.5 Zener Diodes 63
2.7.1.6 VVC Diodes 64
2.7.1.7 Tunnel Diodes 64
2.7.1.8 PIN Diodes 65
2.7.1.9 Schottky Barrier Diodes 65
2.7.1.10 Thyristors 65
2.7.2 Transistors 67
2.7.2.1 Bipolar Junction Transistors 67
2.7.2.2 Field-Effect Transistors 69
2.7.2.3 The MOSFET 70
2.7.2.4 The Junction Field Effect Transistor 71
2.8 Light Emitters and Displays 74
2.8.1 Light-Emitting Diodes 75
2.8.2 Lasers 76
Trang 102.8.3 Liquid Crystal Displays 78
2.8.4 Plasma Displays 79
2.9 Light Sensors 79
2.9.1 Photoresistors 80
2.9.2 Photodiodes 80
2.9.3 Phototransistor 81
2.9.4 Photo-Field Effect Transistor 81
2.9.5 Photocells 82
2.9.6 Charge-Coupled Device 82
2.9.7 Applications of Optically Coupled Devices 83
Problems 84
3 Modeling of Mechatronic Systems 91
Study Objectives 91
3.1 Introduction 91
3.2 Dynamic Systems and Models 92
3.2.1 Terminology 92
3.2.2 Dynamic Models 93
3.2.2.1 Model Complexity 93
3.2.2.2 Model Types 93
3.2.2.3 Types of Analytical Models 94
3.2.2.4 Principle of Superposition 95
3.2.3 Lumped Model of a Distributed System 95
3.2.3.1 Heavy Spring 96
3.3 Lumped Elements and Analogies 98
3.3.1 Across Variables and through Variables 99
3.3.2 Natural Oscillations 100
3.4 Analytical Model Development 100
3.4.1 Steps of Model Development 101
3.4.2 Input–Output Models 102
3.4.3 State-Space Models 102
3.4.3.1 Linear State Equations 102
3.5 Model Linearization 111
3.5.1 Linearization about an Operating Point 111
3.5.2 Function of Two Variables 113
3.5.3 Reduction of System Nonlinearities 114
3.5.4 Linearization Using Experimental Operating Curves 120
3.5.4.1 Torque–Speed Curves of Motors 120
3.5.4.2 Linear Models for Motor Control 120
3.6 Linear Graphs 122
3.6.1 Variables and Sign Convention 123
3.6.1.1 Sign Convention 123
3.6.2 Linear Graph Elements 125
3.6.2.1 Single-Port Elements 125
3.6.2.2 Two-Port Elements 127
3.6.3 Linear Graph Equations 131
3.6.3.1 Compatibility (Loop) Equations 131
3.6.3.2 Continuity (Node) Equations 132
Trang 113.6.4 State Models from Linear Graphs 132
3.6.4.1 System Order 133
3.6.4.2 Sign Convention 133
3.6.4.3 General Observation 134
3.6.4.4 Linear Graph Representation 140
3.6.5 Linear Graphs of Thermal Systems 146
3.7 Transfer Functions and Frequency-Domain Models 148
3.7.1 Transfer Function 149
3.7.2 Frequency-Domain Models 150
3.7.2.1 Frequency Transfer Function (Frequency Response Function) 150
3.7.2.2 Bode Diagram (Bode Plot) and Nyquist Diagram 152
3.7.3 Transfer Functions of Electromechanical Systems 153
3.7.3.1 Mechanical Transfer Functions 154
3.7.3.2 Transfer Functions of Basic Elements 156
3.8 Equivalent Circuits and Linear Graph Reduction 158
3.8.1 Thevenin’s Theorem for Electrical Circuits 159
3.8.2 Mechanical Circuit Analysis Using Linear Graphs 162
3.9 Block Diagrams 169
3.9.1 Simulation Block Diagrams 171
3.9.2 Principle of Superposition 172
3.9.3 Causality and Physical Realizability 172
3.10 Response Analysis 173
3.10.1 Analytical Solution 173
3.10.1.1 Homogeneous Solution 173
3.10.1.2 Particular Solution 174
3.10.1.3 Convolution Integral 174
3.10.1.4 Stability 175
3.10.2 First-Order Systems 175
3.10.3 Second-Order Systems 176
3.10.3.1 Free Response of Undamped Oscillator 176
3.10.3.2 Free Response of Damped Oscillator 177
3.10.3.3 Forced Response of Damped Oscillator 177
3.10.4 Response Using Laplace Transform 180
3.10.4.1 Step Response Using Laplace Transforms 180
3.10.4.2 Incorporation of Initial Conditions 181
3.10.4.3 Step Response of a First-Order System 182
3.10.5 Determination of Initial Conditions for Step Response 182
3.11 Computer Simulation 186
3.11.1 Use of Simulink® in Computer Simulation 187
3.11.1.1 Starting Simulink® 188
3.11.1.2 Basic Elements 188
3.11.1.3 Building an Application 189
3.11.1.4 Running a Simulation 189
Problems 193
4 Component Interconnection and Signal Conditioning 229
Study Objectives 229
4.1 Introduction 229
Trang 124.2 Impedance Characteristics 230
4.2.1 Cascade Connection of Devices 231
4.2.1.1 Output Impedance 231
4.2.1.2 Input Impedance 231
4.2.1.3 Cascade Connection 232
4.2.2 Impedance Matching 234
4.2.3 Impedance Matching in Mechanical Systems 235
4.3 Ampli ers 237
4.3.1 Operational Ampli er 238
4.3.1.1 Use of Feedback in Op-Amps 241
4.3.2 Voltage and Current Ampli ers 242
4.3.3 Instrumentation Ampli ers 243
4.3.3.1 Differential Ampli er 243
4.3.3.2 Common Mode 245
4.3.4 Ampli er Performance Ratings 246
4.3.4.1 Common-Mode Rejection Ratio 247
4.3.4.2 AC-Coupled Ampli ers 249
4.3.5 Ground Loop Noise 249
4.4 Filters 251
4.4.1 Passive Filters and Active Filters 252
4.4.1.1 Number of Poles 253
4.4.2 Low-Pass Filters 253
4.4.2.1 Low-Pass Butterworth Filter 254
4.4.3 High-Pass Filters 255
4.4.4 Band-Pass Filters 256
4.4.4.1 Resonance-Type Band-Pass Filters 257
4.4.4.2 Band-Reject Filters 257
4.4.5 Digital Filters 258
4.4.5.1 Software and Hardware Implementations 259
4.5 Modulators and Demodulators 260
4.5.1 Amplitude Modulation 262
4.5.1.1 Modulation Theorem 263
4.5.1.2 Side Frequencies and Side Bands 263
4.5.2 Application of Amplitude Modulation 264
4.5.2.1 Fault Detection and Diagnosis 266
4.5.3 Demodulation 267
4.6 Analog-to-Digital Conversion 267
4.6.1 Digital-to-Analog Conversion 270
4.6.1.1 Weighted Resistor DAC 271
4.6.1.2 Ladder DAC 272
4.6.1.3 DAC Error Sources 274
4.6.2 Analog-to-Digital Conversion 276
4.6.2.1 Successive Approximation ADC 276
4.6.2.2 Dual Slope ADC 278
4.6.2.3 Counter ADC 280
4.6.2.4 ADC Performance Characteristics 281
4.6.3 Sample-and-Hold Circuitry 284
4.6.4 Multiplexers 285
4.7 Bridge Circuits 286
Trang 134.7.1 Wheatstone Bridge 286
4.7.2 Constant-Current Bridge 288
4.7.3 Hardware Linearization of Bridge Outputs 290
4.7.4 Bridge Ampli ers 290
4.7.5 Half-Bridge Circuits 290
4.7.6 Impedance Bridges 291
4.7.6.1 Owen Bridge 292
4.7.6.2 Wien-Bridge Oscillator 293
Problems 293
5 Instrument Ratings and Error Analysis 303
Study Objectives 303
5.1 Introduction 303
5.1.1 Parameters for Performance Speci cation 304
5.1.2 Perfect Measurement Device 304
5.2 Linearity 304
5.2.1 Saturation 305
5.2.2 Dead Zone 306
5.2.3 Hysteresis 306
5.2.4 The Jump Phenomenon 306
5.2.5 Limit Cycles 306
5.2.6 Frequency Creation 307
5.3 Instrument Ratings 307
5.3.1 Rating Parameters 308
5.4 Bandwidth 310
5.4.1 Transmission Level of a Band-Pass Filter 311
5.4.2 Effective Noise Bandwidth 311
5.4.3 Half-Power (or 3 dB) Bandwidth 311
5.4.4 Fourier Analysis Bandwidth 312
5.4.5 Useful Frequency Range 312
5.4.6 Instrument Bandwidth 313
5.4.7 Control Bandwidth 313
5.4.8 Static Gain 313
5.5 Signal Sampling and Aliasing Distortion 314
5.5.1 Sampling Theorem 314
5.5.2 Anti-Aliasing Filter 315
5.5.3 Another Illustration of Aliasing 317
5.6 Bandwidth Design of a Control System 320
5.6.1 Comment about Control Cycle Time 320
5.7 Instrument Error Analysis 320
5.7.1 Statistical Representation 322
5.7.2 Accuracy and Precision 322
5.7.3 Error Combination 323
5.7.4 Absolute Error 325
5.7.5 SRSS Error 325
5.8 Statistical Process Control 328
5.8.1 Control Limits or Action Lines 329
5.8.2 Steps of SPC 329
Problems 330
Trang 146 Sensors and Transducers 341
Study Objectives 341
6.1 Introduction 341
6.1.1 Terminology 342
6.1.2 Motion Sensors and Transducers 344
6.2 Potentiometer 345
6.2.1 Performance Considerations 346
6.2.2 Optical Potentiometer 348
6.3 Variable-Inductance Transducers 350
6.3.1 Mutual-Induction Transducers 350
6.3.2 Linear-Variable Differential Transformer 351
6.3.2.1 Phase Shift and Null Voltage 353
6.3.2.2 Signal Conditioning 353
6.3.3 Resolver 357
6.3.3.1 Demodulation 358
6.3.4 Self-Induction Transducers 359
6.3.5 Eddy Current Transducers 360
6.3.6 Permanent-Magnet Tachometers 362
6.3.7 DC Tachometer 362
6.3.7.1 Electronic Commutation 363
6.3.7.2 Loading Considerations 363
6.3.8 Permanent-Magnet AC Tachometer 364
6.3.9 AC Induction Tachometer 364
6.4 Variable-Capacitance Transducers 365
6.4.1 Capacitive Rotation Sensor 366
6.4.2 Capacitive Displacement Sensor 367
6.4.3 Capacitance Bridge Circuit 368
6.5 Piezoelectric Sensors 369
6.5.1 Sensitivity 370
6.5.2 Types of Accelerometers 371
6.5.3 Piezoelectric Accelerometer 372
6.5.4 Charge Ampli er 374
6.6 Strain Gages 376
6.6.1 Equations for Strain Gage Measurements 376
6.6.1.1 Bridge Sensitivity 379
6.6.1.2 The Bridge Constant 379
6.6.1.3 Calibration Constant 380
6.6.1.4 Data Acquisition 381
6.6.1.5 Accuracy Considerations 381
6.6.2 Semiconductor Strain Gages 382
6.7 Torque Sensors 385
6.7.1 Strain Gage Torque Sensors 386
6.7.2 Force Sensors 390
6.8 Tactile Sensing 391
6.8.1 Tactile Sensor Requirements 391
6.8.2 Construction and Operation of Tactile Sensors 394
6.8.3 Optical Tactile Sensors 396
6.8.4 Piezoresistive Tactile Sensors 398
6.8.5 Dexterity 398
Trang 156.9 Gyroscopic Sensors 398
6.9.1 Rate Gyro 399
6.9.2 Coriolis Force Devices 400
6.10 Optical Sensors and Lasers 400
6.10.1 Fiber-Optic Position Sensor 401
6.10.2 Laser Interferometer 402
6.10.3 Fiber-Optic Gyroscope 403
6.10.4 Laser Doppler Interferometer 404
6.11 Ultrasonic Sensors 405
6.11.1 Magnetostrictive Displacement Sensors 407
6.12 Thermo-Fluid Sensors 407
6.12.1 Pressure Sensors 408
6.12.2 Flow Sensors 409
6.12.3 Temperature Sensors 412
6.12.3.1 Thermocouple 412
6.12.3.2 Resistance Temperature Detector 413
6.12.3.3 Thermistor 413
6.12.3.4 Bimetal Strip Thermometer 413
6.13 Digital Transducers 414
6.13.1 Advantages of Digital Transducers 415
6.13.2 Shaft Encoders 415
6.13.2.1 Encoder Types 415
6.13.3 Incremental Optical Encoder 416
6.13.3.1 Direction of Rotation 419
6.13.3.2 Hardware Features 419
6.13.3.3 Displacement Measurement 421
6.13.3.4 Digital Resolution 421
6.13.3.5 Physical Resolution 422
6.13.3.6 Step-Up Gearing 422
6.13.3.7 Interpolation 423
6.13.3.8 Velocity Measurement 424
6.13.3.9 Velocity Resolution 424
6.13.3.10 Step-Up Gearing 427
6.13.3.11 Data Acquisition Hardware 428
6.13.4 Absolute Optical Encoders 429
6.13.4.1 Gray Coding 430
6.13.4.2 Code Conversion Logic 431
6.13.4.3 Advantages and Drawbacks 432
6.13.5 Encoder Error 432
6.13.5.1 Eccentricity Error 433
6.14 Miscellaneous Digital Transducers 434
6.14.1 Digital Resolvers 434
6.14.2 Digital Tachometers 435
6.14.3 Hall-Effect Sensors 436
6.14.4 Linear Encoders 438
6.14.5 Moiré Fringe Displacement Sensors 439
6.14.6 Binary Transducers 441
6.14.7 Other Types of Sensors 444
Trang 166.15 Image Sensors 444
6.15.1 Image Processing and Computer Vision 444
6.15.2 Image-Based Sensory System 445
6.15.2.1 Camera 445
6.15.2.2 Image Frame Acquisition 445
6.15.2.3 Color Images 446
6.15.3 Image Processing 446
6.15.4 Some Applications 447
Problems 447
7 Actuators 465
Study Objectives 465
7.1 Introduction 465
7.2 Stepper Motors 466
7.2.1 Stepper Motor Classi cation 466
7.2.2 Hybrid Stepper Motor 467
7.2.3 Microstepping 469
7.2.4 Driver and Controller 470
7.2.5 Driver Hardware 472
7.2.6 Stepper Motor Selection 474
7.2.6.1 Torque Characteristics and Terminology 474
7.2.6.2 Stepper Motor Selection Process 476
7.2.6.3 Positioning (x–y) Tables 478
7.2.7 Stepper Motor Applications 484
7.3 DC Motors 486
7.3.1 Rotor and Stator 487
7.3.2 Commutation 488
7.3.3 Brushless DC Motors 489
7.3.4 DC Motor Equations 489
7.3.4.1 Steady-State Characteristics 491
7.3.5 Experimental Model for DC Motor 492
7.3.5.1 Electrical Damping Constant 492
7.3.5.2 Linearized Experimental Model 493
7.3.6 Control of DC Motors 494
7.3.6.1 Armature Control 494
7.3.6.2 Motor Time Constants 495
7.3.6.3 Field Control 496
7.3.7 Feedback Control of DC Motors 498
7.3.7.1 Velocity Feedback Control 498
7.3.7.2 Position Plus Velocity Feedback Control 498
7.3.7.3 Position Feedback with PID Control 499
7.3.8 Motor Driver 500
7.3.8.1 Interface Board 500
7.3.8.2 Drive Unit 501
7.3.9 DC Motor Selection 504
7.3.9.1 Motor Data and Speci cations 504
7.3.9.2 Selection Considerations 505
Trang 177.3.9.3 Motor Sizing Procedure 506
7.3.9.4 Inertia Matching 507
7.3.9.5 Drive Ampli er Selection 508
7.4 Induction Motors 510
7.4.1 Rotating Magnetic Field 511
7.4.2 Induction Motor Characteristics 512
7.4.3 Torque–Speed Relationship 514
7.4.4 Induction Motor Control 518
7.4.4.1 Excitation Frequency Control 518
7.4.4.2 Voltage Control 520
7.4.4.3 Field Feedback Control (Flux Vector Drive) 523
7.4.5 A Transfer-Function Model for an Induction Motor 523
7.4.6 Single-Phase AC Motors 525
7.5 Miscellaneous Actuators 526
7.5.1 Synchronous Motors 526
7.5.1.1 Control of a Synchronous Motor 527
7.5.2 Linear Actuators 527
7.5.2.1 Solenoid 527
7.5.2.2 Linear Motors 529
7.6 Hydraulic Actuators 530
7.6.1 Components of a Hydraulic Control System 531
7.6.2 Hydraulic Pumps and Motors 532
7.6.3 Hydraulic Valves 535
7.6.3.1 Spool Valve 536
7.6.3.2 Steady-State Valve Characteristics 538
7.6.4 Hydraulic Primary Actuators 541
7.6.5 The Load Equation 542
7.6.6 Hydraulic Control Systems 543
7.6.6.1 Feedback Control 549
7.6.7 Constant-Flow Systems 552
7.6.8 Pump-Controlled Hydraulic Actuators 553
7.6.9 Hydraulic Accumulators 553
7.6.10 Pneumatic Control Systems 554
7.6.10.1 Flapper Valves 554
7.6.11 Hydraulic Circuits 557
Problems 558
8 Digital Hardware and Microcontrollers 579
Study Objectives 579
8.1 Introduction 579
8.2 Number Systems and Codes 580
8.2.1 Binary Representation 580
8.2.2 Negative Numbers 582
8.2.2.1 Signed Magnitude Representation 582
8.2.2.2 Two’s Complement Representation 582
8.2.2.3 One’s Complement 583
8.2.3 Binary Multiplication and Division 583
8.2.4 Binary Gray Codes 583
Trang 188.2.5 Binary Coded Decimal 584
8.2.6 ASCII (Askey) Code 584
8.3 Logic and Boolean Algebra 585
8.3.1 Logic 585
8.3.1.1 Negation 585
8.3.1.2 Disjunction 585
8.3.1.3 Conjunction 585
8.3.1.4 Implication 586
8.3.2 Boolean Algebra 587
8.3.2.1 Sum and Product Forms 588
8.4 Combinational Logic Circuits 588
8.4.1 Logic Gates 588
8.4.2 IC Logic Families 591
8.4.3 Design of Logic Circuits 592
8.4.3.1 Multiplexer Circuit 593
8.4.3.2 Adder Circuits 593
8.4.3.3 Active-Low Signals 594
8.4.4 Minimal Realization 596
8.4.4.1 Karnaugh Map Method 596
8.5 Sequential Logic Devices 598
8.5.1 RS Flip-Flop 599
8.5.2 Latch 600
8.5.3 JK Flip-Flop 600
8.5.4 D Flip-Flop 602
8.5.4.1 Shift Register 602
8.5.5 T Flip-Flop and Counters 603
8.5.6 Schmitt Trigger 606
8.6 Practical Considerations of IC Chips 607
8.6.1 IC Chip Production 607
8.6.2 Chip Packaging 608
8.6.3 Applications 609
8.7 Microcontrollers 609
8.7.1 Microcontroller Architecture 609
8.7.1.1 Microcontroller Operation 610
8.7.2 Microprocessor 611
8.7.2.1 Arithmetic Logic Unit 611
8.7.2.2 Program Counter 612
8.7.2.3 Address Register 612
8.7.2.4 Accumulator and Data Register 613
8.7.2.5 Instruction Register 613
8.7.2.6 Operation Decoder 613
8.7.2.7 Sequencer 613
8.7.3 Memory 613
8.7.3.1 RAM, ROM, PROM, EPROM, and EEPROM 613
8.7.3.2 Bits, Bytes, and Words 614
8.7.3.3 Volatile Memory 614
8.7.3.4 Physical Form of Memory 614
8.7.3.5 Memory Access 615
8.7.3.6 Memory Card Design 617
Trang 198.7.4 Input/Output Hardware 619
8.7.4.1 Microcontroller Pin-Out 620
8.7.4.2 Programmed I/O 620
8.7.4.3 Interrupt I/O 622
8.7.4.4 Direct Memory Access Method 622
8.7.4.5 Handshaking Operation 623
8.7.4.6 Clock, Counter, and Timer 623
8.7.5 Microcontroller Programming and Program Execution 624
8.7.5.1 Instruction Set, Operation Codes, and Mnemonics 624
8.7.5.2 Programming and Languages 624
8.7.5.3 Program Execution 625
8.7.5.4 Real-Time Processing 626
8.7.6 Development of Microcontroller Applications 627
Problems 628
9 Control Systems 637
Study Objectives 637
9.1 Introduction 637
9.2 Control System Structure 638
9.2.1 Feedback and Feedforward Control 638
9.2.2 Programmable Logic Controllers 640
9.2.2.1 PLC Hardware 641
9.2.3 Distributed Control 642
9.2.3.1 Hierarchical Control 643
9.3 Control System Performance 644
9.3.1 Performance Speci cation in Time Domain 645
9.3.1.1 Simple Oscillator Model 647
9.4 Control Schemes 649
9.4.1 Feedback Control with PID Action 651
9.4.1.1 System Type and Error Constants 654
9.4.2 Performance Speci cation Using s-Plane 655
9.5 Stability 656
9.5.1 Routh–Hurwitz Criterion 657
9.5.1.1 Routh Array 658
9.5.1.2 Auxiliary Equation (Zero-Row Problem) 659
9.5.1.3 Zero Coef cient Problem 660
9.5.1.4 Relative Stability 661
9.5.2 Root Locus Method 662
9.5.2.1 Root Locus Rules 664
9.5.2.2 Steps of Sketching Root Locus 665
9.5.3 Stability in the Frequency Domain 668
9.5.3.1 Marginal Stability 668
9.5.3.2 The 1, 0 Condition 668
9.5.3.3 Phase Margin and Gain Margin 670
9.5.3.4 Bode and Nyquist Plots 671
9.6 Advanced Control 672
9.6.1 Linear Quadratic Regulator Control 673
9.6.2 Modal Control 674
Trang 209.6.3 Nonlinear Feedback Control 675
9.6.4 Adaptive Control 676
9.6.5 Sliding Mode Control 678
9.6.6 Linear Quadratic Gaussian Control 680
9.6.7 H∞ (H-In nity) Control 682
9.7 Fuzzy Logic Control 683
9.7.1 Fuzzy Logic 683
9.7.2 Fuzzy Sets and Membership Functions 684
9.7.3 Fuzzy Logic Operations 685
9.7.3.1 Complement (Negation, NOT) 685
9.7.3.2 Union (Disjunction, OR) 686
9.7.3.3 Intersection (Conjunction, AND) 686
9.7.3.4 Implication (If–Then) 686
9.7.4 Compositional Rule of Inference 687
9.7.4.1 Extensions to Fuzzy Decision Making 688
9.7.5 Basics of Fuzzy Control 689
9.7.6 Fuzzy Control Surface 693
9.8 Digital Control 694
9.8.1 Computer Control Systems 696
9.8.2 Components of a Digital Control System 696
9.8.3 Advantages of Digital Control 697
9.8.4 Computer Implementation 698
Problems 699
10 Case Studies in Mechatronics 713
Study Objectives 713
10.1 Introduction 713
10.2 Engineering Design 713
10.2.1 Engineering Design as an Optimization Problem 714
10.2.2 Useful Terminology 716
10.2.3 Design Projects 717
10.2.4 Quality Function Deployment 718
10.2.5 Design Report 718
10.2.6 Design of a Mechatronic System 720
10.3 Robotics Case Study 720
10.3.1 General Considerations 720
10.3.2 Robot Selection 722
10.3.2.1 Commercial Robots 723
10.3.3 Robotic Workcells 725
10.3.4 Robot Design and Development 727
10.3.4.1 Prototype Robot 727
10.3.4.2 Robot Design 728
10.3.4.3 Actuator Selection/Sizing 729
10.3.4.4 Final Design 731
10.3.4.5 Ampli ers and Power Supplies 733
10.3.4.6 Control System 734
10.3.4.7 Economic Analysis 736
Trang 2110.4 Iron Butcher Case Study 737
10.4.1 Technology Needs 737
10.4.2 Final Design 738
10.4.3 Control System Architecture 740
10.4.3.1 Motor Control Console 740
10.4.3.2 Junction Box 741
10.4.4 Hydraulic System 741
10.4.4.1 Physical Parameters of the Cutter Table 742
10.4.4.2 Hydraulic Piston Parameters 742
10.4.4.3 Flow Control Servovalves 742
10.4.4.4 Pilot Valves 745
10.4.4.5 Position Transducers 745
10.4.5 Pneumatic System 745
10.4.6 Economic Analysis 745
10.4.7 Networked Application 747
10.5 Exercises 748
10.6 Projects 749
10.6.1 Project 1: Automated Glue Dispensing System 749
10.6.2 Project 2: Material Testing Machine 749
10.6.3 Project 3: Active Orthosis 750
10.6.4 Project 4: Railway Car Braking System 750
10.6.5 Project 5: Machine Tool Control System 750
10.6.6 Project 6: Welding Robot 751
10.6.7 Project 7: Wood Strander 751
10.6.8 Project 8: Automated Mining Shovel 752
10.6.9 Project 9: Can-Filling Machine 753
10.6.10 Project 10: Fish-Marking Machine 753
10.6.11 Project 11: Machine for Grading Herring Roe 754
10.6.12 Project 12: Hydraulic Control System 755
Appendix A: Solid Mechanics 757
A.1 General Problem of Elasticity 757
A.1.1 Strain Components 757
A.1.2 Constitutive Equations 757
A.1.3 Equilibrium Equations 758
A.1.4 Compatibility Equations 758
A.2 Plane Strain Problem 758
A.2.1 Constitutive Equations 759
A.2.2 Equilibrium Equations 759
A.3 Plane Stress Problem 759
A.3.1 Constitutive Equations 760
A.3.2 Equilibrium Equations 760
A.3.3 Plane Stress Problem in Polar Coordinates 760
A.3.3.1 Strain Components 760
A.3.3.2 Constitutive Equations 761
A.3.3.3 Equilibrium Equations 761
A.4 Rotating Members 761
A.4.1 Rotating Disks 761
Trang 22A.4.2 Rotating Thick Cylinders 762
A.4.2.1 Strain Equations 763A.4.2.2 Stress–Strain (Constitutive) Relations 763A.4.2.3 Equilibrium Equations 763A.4.2.4 Final Result 764A.4.2.5 Temperature Stresses 764A.4.3 Particular Cases of Cylinders 764
A.4.3.1 Case 1: Axially Restrained Ends 764A.4.3.2 Case 2: Thick Pressure Vessel 765A.4.3.3 Case 3: Thin Pressure Vessel 765A.4.3.4 Case 4: Rotating Cylinder with Free Ends 765A.5 Mohr’s Circle of Plane Stress 766A.6 Torsion 767A.6.1 Circular Members 767A.6.2 Torque Sensor 769A.7 Beams in Bending and Shear 772A.7.1 Mohr’s Theorems 772A.7.2 Maxwell’s Theorem of Reciprocity 772A.7.3 Castigliano’s First Theorem 773A.7.4 Elastic Energy of Bending 773A.8 Open-Coiled Helical Springs 773A.8.1 Case 1: Axial Load W 773A.8.2 Case 2: Axial Couple M 775A.9 Circular Plates with Axisymmetric Loading 776A.9.1 Strains 776A.9.2 Stresses 776A.9.3 Moments 776A.9.4 Equilibrium Equations 777A.9.5 Boundary Conditions 778
A.9.5.1 Fixed Edge 778A.9.5.2 Simply Supported Edge 778A.9.5.3 Partially Restrained Edge 778
Appendix B: Transform Techniques 779B.1 Laplace Transform 779B.1.1 Laplace Transforms of Some Common Functions 780
B.1.1.1 Laplace Transform of a Constant 780B.1.1.2 Laplace Transform of the Exponential 780B.1.1.3 Laplace Transform of Sine and Cosine 781B.1.1.4 Laplace Transform of a Derivative 782B.1.2 Table of Laplace Transforms 783B.2 Response Analysis 785B.3 Transfer Function 790B.4 Fourier Transform 792B.4.1 Frequency-Response Function (Frequency Transfer Function) 793B.5 The s-Plane 793B.5.1 An Interpretation of Laplace and Fourier Transforms 794B.5.2 Application in Circuit Analysis 794
Trang 23Appendix C: Probability and Statistics 797C.1 Probability Distribution 797C.1.1 Cumulative Probability Distribution Function 797C.1.2 Probability Density Function 797C.1.3 Mean Value (Expected Value) 798C.1.4 Root-Mean-Square Value 798C.1.5 Variance and Standard Deviation 798C.1.6 Independent Random Variables 799C.1.7 Sample Mean and Sample Variance 800C.1.8 Unbiased Estimates 800C.1.9 Gaussian Distribution 802C.1.10 Con dence Intervals 803C.2 Sign Test and Binomial Distribution 806C.3 Least Squares Fit 808Appendix D: Software Tools 813
D.2.1 Computations 813
D.2.1.1 Arithmetic 814D.2.1.2 Arrays 814D.2.2 Relational and Logical Operations 815D.2.3 Linear Algebra 816D.2.4 M-Files 817D.3 Control Systems Toolbox 817D.3.1 Compensator Design Example 817
D.3.1.1 Building the System Model 820D.3.1.2 Importing Model into SISO Design Tool 820D.3.1.3 Adding Lead and Lag Compensators 820D.3.2 PID Control with Controller Tuning 821
D.3.2.1 Proportional Control 821D.3.2.2 PI Control 821D.3.2.3 PID Control 824D.3.3 Root Locus Design Example 825D.4 Fuzzy Logic Toolbox 825D.4.1 Graphical Editors 828D.4.2 Command Line–Driven FIS Design 828D.4.3 Practical Stand-Alone Implementation in C 829D.5 LabVIEW 829D.5.1 Introduction 830D.5.2 Some Key Concepts 830D.5.3 Working with LabVIEW 831
D.5.3.1 Front Panel 832D.5.3.2 Block Diagrams 832D.5.3.3 Tools Palette 834D.5.3.4 Controls Palette 834D.5.3.5 Functions Palette 834Index 837
Trang 24mecha-Mechatronics concerns the synergistic and concurrent use of mechanics, electronics, computer engineering, and intelligent control systems in modeling, analyzing, design-ing, developing, implementing, and controlling smart electromechanical products As modern machinery and electromechanical devices are typically being controlled using analog and digital electronics and computers, the technologies of mechanical engineer-ing in such a system can no longer be isolated from those of electronic and computer engineering For example, in a robotic system or a micromachine, mechanical compo-nents are integrated and embedded with analog and digital electronic components and microcontrollers to provide single functional units or products Similarly, devices with embedded and integrated sensing, actuation, signal processing, and control have many practical advantages In the framework of mechatronics, a uni ed approach is taken to integrate different types of components and functions, both mechanical and electrical, in modeling, analysis, design, implementation, and control, with the objective of harmoni-ous operation that meets a desired set of performance speci cations in a rather “optimal” manner, resulting in bene ts with regard to performance, ef ciency, reliability, cost, and environmental impact.
Mechatronics has emerged as a bona de eld of practice, research, and development, and simultaneously as an academic discipline in engineering Historically, the approach taken in learning a new eld of engineering has been to rst concentrate on a single branch of engineering, such as electrical, mechanical, civil, chemical, or aerospace engi-neering, in an undergraduate program and then learn the new concepts and tools dur-ing practice, graduate study, or research Since the discipline of mechatronics involves electronic and electrical engineering, mechanical and materials engineering, and con-trol and computer engineering, a more appropriate approach would be to acquire a strong foundation in the necessary fundamentals from these various branches of engi-neering in an integrated manner in a single and uni ed undergraduate curriculum In fact, many universities in the United States, Canada, Europe, Asia, and Australia have established both undergraduate and graduate programs in mechatronics This book is focused toward an integrated education and practice as related to electromechanical systems
Scope of the Book
The book is an outgrowth of my experience in integrating key components of tronics into senior-level courses for engineering students, and in teaching graduate and
Trang 25mecha-professional courses in mechatronics and related topics The material in the book has acquired an application orientation through industrial experience I have gained at orga-nizations such as IBM Corporation, Westinghouse Electric Corporation, Bruel and Kjaer, and NASA’s Lewis and Langley Research Centers To maintain clarity and the focus and
to maximize the usefulness of the book, I have presented the material in a manner that will be convenient and useful to anyone with a basic engineering background, be it elec-trical, mechanical, aerospace, control, or computer engineering Case studies, detailed worked examples, and exercises are provided throughout the book Complete solutions to the end-of-chapter problems are presented in a “Solutions Manual,” which will be avail-able to instructors who take up a detailed study of the book
The book consists of 10 chapters and 4 appendices The chapters are devoted to senting the fundamentals in electrical and electronic engineering, mechanical engineer-ing, control engineering, and computer engineering, which are necessary for forming the foundation of mechatronics In particular, they cover mechanical components, electrical and electronic components, modeling, analysis, instrumentation, sensors, transducers, sig-nal processing, actuators, control, and system design and integration The book uniformly incorporates the underlying fundamentals into analytical methods, modeling approaches, and design techniques in a systematic manner throughout the main chapters The practical application of the concepts, approaches, and tools presented in the introductory chapters are demonstrated through a wide range of practical examples and a comprehensive set of case studies The background theory and techniques that are not directly useful to present the fundamentals of mechatronics are provided in a concise manner in the appendices Also, in the Solutions Manual, a curriculum is suggested for an undergraduate degree in mechatronics
pre-Main Features of the Book
The following are the main features of the book, which will distinguish it from other books on the same topic:
Readability and convenient reference are given priority in the presentation and
•
formatting of the book
Key concepts and formulas developed and presented in the book are
ations and the practice of mechatronics
Numerous problems and exercises, most of which are based on practical situations
•
and applications, and convey additional useful information on mechatronics, are provided at the end of each chapter
The use of MATLAB
described, and a variety of illustrative examples are provided for their use Many
Trang 26problems in the book are cast for solution using these computer tools However, the main goal of the book is not simply to train the students in the use of software tools Instead, a thorough understanding of the core and foundation of the sub-ject, as facilitated by the book, will enable the student to learn the fundamentals and engineering methodologies behind the software tools: the choice of proper tools to solve a given problem, interpret the results generated by them, assess the validity and correctness of the results, and understand the limitations of the available tools.
The material is presented in a manner so that users from diverse engineering
provided separately in four appendices at the end of the book
An Instructor’s Manual (Solutions Manual) is available, which provides
Mechatronic devices and components
Sensors and actuators
Electromechanical systems
System modeling and simulation
Control system instrumentation
Mechatronic system instrumentation
Further material on these topics can be found in the following textbooks (with solutions manuals):
de Silva, C.W., Sensors and Actuators—Control System Instrumentation, CRC Press/Taylor & Francis, Boca Raton, FL, 2007
de Silva, C.W., Modeling and Control of Engineering Systems, CRC Press/Taylor & Francis, Boca Raton, FL, 2009
Trang 27For MATLAB® and Simulink® product information, please contact
The MathWorks, Inc
3 Apple Hill Drive
Natick, MA, 01760-2098 USA
Tel: 508-647-7000
Fax: 508-647-7001
E-mail: info@mathworks.com
Web: www.mathworks.com
LabVIEW™ is a product of National Instruments, Inc, Austin, TX
I have personally used these software tools for teaching and for the development of this book
Clarence W de SilvaVancouver, British Columbia, Canada
Trang 28Many individuals have assisted in the preparation of this book, but it is not practical to acknowledge all such assistance here First, I wish to recognize the contributions, both direct and indirect, of my graduate students, research associates, and technical staff Particular mention should be made of my PhD student, Roland H Lang, whose research assistance has been very important I am particularly grateful to Jonathan W Plant, senior editor, CRC Press/Taylor & Francis, for his interest, enthusiasm, and strong support throughout the project Others at CRC Press and its af liates, in particular, Christine Selvan, Joette Lynch, Anithajohny Mariasusai, Jessica Vakili, and others for their ne effort in produc-ing this book I also wish to acknowledge the advice and support of various authorities
in the eld—particularly, Professor Devendra Garg of Duke University; Professor Madan Gupta of the University of Saskatchewan; Professor Mo Jamshidi of the University of Texas (San Antonio, Texas); Professors Ben Chen, Tong-Heng Lee, and Kok-Kiong Tan of the National University of Singapore; Professor Maoqing Li of Xiamen University; Professor Max Meng of the Chinese University of Hong Kong; Dr Daniel Repperger of the U.S Air Force Research Laboratory; and Professor David N Wormley of the Pennsylvania State University Finally, I owe an apology to my wife and children for the unintentional
“neglect” that they may have faced during the latter stages of the preparation of this book and am grateful for all their support
Trang 30Clarence W de Silva, PE, fellow ASME, fellow IEEE, fellow Royal Society of Canada, is
a professor of mechanical engineering at the University of British Columbia, Vancouver, Canada, and occupies the Tier 1 Canada Research Chair professorship in mechatronics and industrial automation Prior to this he occupied the Natural Sciences and Engineering Research Council–British Columbia Packers Research Chair in Industrial Automation since 1988 He served as a faculty member at Carnegie Mellon University (1978–1987) and
as a Fulbright visiting professor at the University of Cambridge, Cambridge, England (1987–1988)
Professor de Silva received two PhD degrees from the Massachusetts Institute of Technology (1978) and the University of Cambridge, England (1998), and an honorary DEng from the University of Waterloo, Waterloo, Ontario, Canada (2008) Dr de Silva also occupied the Mobil Endowed Chair professorship in the Department of Electrical and Computer Engineering at the National University of Singapore and the honorary chair professorship of the National Taiwan University of Science and Technology
Other fellowships include the Fellow Canadian Academy of Engineering, Lilly Fellow, NASA-ASEE Fellow, Senior Fulbright Fellow to Cambridge University, Fellow of the Advanced Systems Institute of BC, Killam Fellow, and Erskine Fellow
Professor de Silva has received the Paynter Outstanding Investigator Award and Takahashi Education Award, ASME Dynamic Systems & Control Division; Killam Research Prize; Outstanding Engineering Educator Award, IEEE Canada; and the Lifetime Achievement Award, World Automation Congress He has also received the IEEE Third Millennium Medal; Meritorious Achievement Award, Association of Professional Engineers of BC; Outstanding Contribution Award, IEEE Systems, Man, and Cybernetics Society He has given 20 keynote addresses
He has served on 14 journals including IEEE Transactions on Control System Technology; the Journal of Dynamic Systems, Measurement & Control; and Transactions of ASME; edi-tor in chief, the International Journal of Control and Intelligent Systems and the International Journal of Knowledge-Based Intelligent Engineering Systems Other editorial duties include senior technical editor, Measurements and Control; and regional editor, North America, Engineering Applications of Arti cial Intelligence—IFAC International Journal of Intelligent Real-Time Automation
Professor de Silva has published 19 technical books, 18 edited books, 44 book chapters, about 200 journal articles, and over 215 conference papers
In the areas of research and development, he has been involved in industrial process monitoring and automation, intelligent multi-robot cooperation, mechatronics, intelligent control, sensors, actuators, and control system instrumentation, with funding of about $7 million, as principal investigator, during the past 15 years
Trang 32electron-Mechatronic products and systems include modern automobiles and aircraft, smart household appliances, medical robots, space vehicles, and of ce automation devices In this chapter, the subject of mechatronics is introduced, important issues in modeling, design, and the development of a mechatronic product or system are highlighted, and the associated technology areas and applications are indicated.
Trang 331.2 Mechatronic Systems
A typical mechatronic system consists of a mechanical skeleton, actuators, sensors, lers, signal conditioning/modi cation devices, computer/digital hardware and software, interface devices, and power sources Different types of sensing, information acquisition, and transfer are involved among all these various types of components For example, a servomotor, which is a motor with the capability of sensory feedback for accurate genera-tion of complex motions, consists of mechanical, electrical, and electronic components (see Figure 1.1) The main mechanical components are the rotor, stator, and the bearings The electrical components include the circuitry for the eld windings and rotor windings (not in the case of permanent-magnet rotors) and the circuitry for power transmission and commutation (if needed) Electronic components include those needed for sensing (e.g., an optical encoder for displacement and speed sens-
control-ing and a tachometer for speed senscontrol-ing) The overall design
of a servomotor can be improved by taking a mechatronic
approach
The humanoid robot shown in Figure 1.2a is a more
com-plex and “intelligent” mechatronic system It may involve
many servomotors and a variety of mechatronic
compo-nents, as is clear from the sketch in Figure 1.2b A
mecha-tronic approach can greatly bene t the analysis/modeling,
design, and development of a complex electromechanical
system of this nature
In the computer industry, hard-disk drives (HDD; see
Figure 1.3), devices for disk retrieval, access and ejection,
and other electromechanical components can considerably
bene t from high-precision mechatronics The impact goes
FIGURE 1.1
A servomotor is a mechatronic device (Courtesy of Danaher Motion, Rockford, IL.)
Six-axis force sensor
Six-axis force sensor
Wireless receiver
Gyro G-force sensor Battery CPU Antenna
Actuator auxiliary processing units
Actuator auxiliary processing units
Trang 34further because digital computers are integrated into a vast variety of other devices and mechatronic applications.
Technology issues of a general mechatronic system are indicated in Figure 1.4 It is seen that they span the traditional elds of mechanical engineering, electrical and electronic engineering, control engineering, and computer engineering Each aspect or issue within
Spindle motor Head slider
Disk
Mounting frame
Arm motor stator
Tracks
Arm rotor
Arm Control circuit
FIGURE 1.3
An HDD unit of a computer.
Modeling, Analysis Integrated design Testing and refinement
Sensors and transducers
Structural
Actuators Controllers
Energy
Hydraulic and pneumatic devices
Signal processing Thermal
Mechanical
System development tasks
Mechatronic system
FIGURE 1.4
Concepts and technologies of a mechatronic system.
Trang 35the system may take a multi-domain character For example, as noted before, an actuator (e.g., dc servo motor) itself may represent a mechatronic device within a larger mecha-tronic system such as an automobile or a robot.
The study of mechatronic engineering should include all stages of modeling, design, development, integration, instrumentation, control, testing, operation, and maintenance
of a mechatronic system
1.3 Modeling and Design
A model is a representation of a real system, and the subject of model development eling) is important in mechatronics (see Chapter 3) Modeling and design can go hand-in-hand in an iterative manner Of course, in the beginning of the design process, the desired system does not exist In this context, a model of the anticipated system can be very useful
(mod-In view of the complexity of a design process, particularly when striving for an optimal design, it is useful to incorporate system modeling as a tool for design iteration particu-larly because prototyping can become very costly and time consuming
In the beginning, by knowing some information about the system (e.g., intended tions, performance speci cations, past experience, and knowledge of related systems) and
func-by using the design objectives, it is possible to develop a model of suf cient (low to erate) detail and complexity By analyzing and carrying out computer simulations of the model, it will be possible to generate useful information that will guide the design process (e.g., the generation of a preliminary design) In this manner, design decisions can be made and the model can be re ned using the available (improved) design This iterative link between modeling and design is schematically shown in Figure 1.5
mod-It is expected that the mechatronic approach will result in a higher quality of the ucts and services, improved performance, and increased reliability while approach-ing some form of optimality This will enable the development and production of
prod-System
Model refinement
Purpose, performance specs,
past knowledge, etc.
Performance prediction
Design objectives/specs
Design decisions
FIGURE 1.5
Link between modeling and design.
Trang 36electromechanical systems ef ciently, rapidly, and economically When performing the integrated design of a mechatronic system, the concepts of energy and power present a unifying thread The reasons are clear First, in an electromechanical system, ports of power and energy exist that link electrical dynamics and mechanical dynamics Hence, the modeling, analysis, and optimization of a mechatronic system can be carried out using a hybrid system (or multi-domain system) formulation (a model) that integrates mechanical aspects and electrical aspects of the system Second, an optimal design will aim for minimal energy dissipation and maximum energy ef ciency There are related implications; for example, greater dissipation of energy will mean reduced overall ef -ciency and increased thermal problems, noise, vibration, malfunctions, wear and tear, and increased environmental impact Again, a hybrid model that presents an accurate picture of the energy/power ow within the system will present an appropriate frame-work for the mechatronic design (Note: Refer to linear graph models in particular, as discussed in Chapter 3.)
A design may use excessive safety factors and worst-case speci cations (e.g., for ical loads and electrical loads) This will not provide an optimal design or may not lead to the most ef cient performance Design for optimal performance may not necessarily lead
mechan-to the most economical (least costly) design, however When arriving at a truly optimal design, an objective function that takes into account all important factors (performance, quality, cost, speed, ease of operation, safety, environmental impact, etc.) has to be opti-mized A complete design process should generate the necessary details for the construc-tion or assembly of the system
1.4 Mechatronic Design Concept
In a true mechatronic sense, the design of a multi-domain multicomponent system will require the simultaneous consideration and integrated design of all its components, as indicated in Figure 1.4 Such an integrated and “concurrent” design will call for a fresh look at the design process itself and also a formal consideration of information and energy transfer between the components within the system
In an electromechanical system, there exists an interaction (or coupling) between trical dynamics and mechanical dynamics Speci cally, electrical dynamics affect the mechanical dynamics and vice versa Traditionally, a “sequential” approach has been adopted to the design of multi-domain (or mixed) systems such as electromechanical sys-tems For example, rst the mechanical and structural components are designed, next the electrical and electronic components are selected or developed and interconnected, then
elec-a computer is selected elec-and interfelec-aced with the system, subsequently elec-a controller is elec-added, and so on The dynamic coupling between various components of a system dictates, how-ever, that an accurate design of the system should consider the entire system as a whole rather than designing the electrical/electronic aspects and the mechanical aspects sepa-rately and sequentially When independently designed components are interconnected, several problems can arise as follows:
1 When two independently designed components are interconnected, the original characteristics and operating conditions of the two will change due to the loading
or dynamic interactions (see Chapter 4)
Trang 372 A perfect matching of two independently designed and developed components will be practically impossible As a result, a component can be considerably under-utilized or overloaded, in the interconnected system, both conditions being inef- cient and undesirable.
3 Some of the external variables in the components will become internal and den” due to interconnection, which can result in potential problems that cannot be explicitly monitored through sensing and cannot be directly controlled
“hid-The need for an integrated and concurrent design for electromechanical systems can be identi ed as a primary motivation for the developments in the eld of mechatronics.1.4.1 Coupled Design
An uncoupled design is where each subsystem is designed separately (and sequentially), while keeping the interactions with the other subsystems constant (i.e., ignoring the dynamic interactions) Mechatronic design involves an integrated or “coupled” design The concept of mechatronic design may be illustrated using an example of an electro-mechanical system, which can be treated as a coupling of an electrical subsystem and a mechanical subsystem An appropriate model for the system is shown in Figure 1.6a Note that the two subsystems are coupled using a loss-free (pure) energy transformer while the losses (energy dissipation) are integral with the subsystems In this system, assume that under normal operating conditions the energy ow is from the electrical subsystem to the mechanical subsystem (i.e., the electrical subsystem behaves like a motor rather than
a generator) At the electrical port that connects to the energy transformer, there exists a current i (a “through” variable) owing in and a voltage v (an “across” variable) with the shown polarity (the concepts of through and across variables and the related terminol-ogy are explained in Chapter 3) The product vi is the electrical power, which is positive out of the electrical subsystem and into the transformer Similarly, at the mechanical port that comes out of the energy transformer, there exists a torque τ (a through variable) and
an angular speed ω (an across variable) with the sign convention indicated in Figure 1.6a Accordingly, a positive mechanical power ωτ ows out of the transformer and into the mechanical subsystem The ideal transformer implies that
Source (fixed)
i v
Trang 38In a conventional uncoupled design of the system, the electrical subsystem is designed
by treating the effects of the mechanical subsystem as a xed load, and the mechanical subsystem is designed by treating the electrical subsystem as a xed energy source, as indicated in Figure 1.6b Suppose that, in this manner, the electrical subsystem achieves an
may be achieved, for example, by minimizing the quadratic cost function:
I
where
D denotes the transformation that represents the design process
p denotes information including system parameters that is available for the designEven though this formulation of the mechatronic design problem appears rather simple and straightforward, the reality is otherwise In particular, the design process, as denoted by the transformation D, can be quite complex and typically nonanalytic Furthermore, mini-mization of the cost function J is by and large an iterative practical scheme and undoubtedly
a knowledge-based and nonanalytic procedure This complicates the process of mechatronic design In any event, the design process will need the information represented by p
1.4.2 Mechatronic Design Quotient
Mechatronic systems are complex and require multiple technologies in multiple domains Their optimal design may call for multiple performance indices The problem of mecha-tronic design may be treated as a maximization of a “mechatronic design quotient” or MDQ In particular, an alternative formulation of the optimization problem given by (1.2) and (1.3) would be the maximization of the MDQ:
Trang 39corresponding indices may be qualitative or nonanalytic and may have correlations or interactions Then, more sophisticated representations (e.g., the use of fuzzy measures) and optimization techniques (e.g., evolutionary computing or genetic programming or GP) may be employed in the design process.
For example, in the use of genetic algorithms (GA) for mechatronic design, we start with
a group (population) of initial chromosomes (embryos) where an individual chromosome
is one possible design An individual gene in a chromosome corresponds to an element of information in a design (e.g., system component, connection structure, set of parameters, design attribute) Alleles are possible values of a gene (e.g., available choices for a par-ticular component) The “ tness function” of the GA represents the “value,” “goodness,”
or “ tness” of a design In the present context, the tness function is the MDQ, which is computable for a given design once the element information of the design is known Then the problem of design optimization becomes:
…
1 2
The strength and applicability of the MDQ approach stem from the possibility that the design process may be hierarchically separated Then, an MDQ may be optimized for one design layer involving two more technology groups in that layer before proceeding
to the next lower design layer where each technology group is separately optimized by considering several technology/component groups within that group together with an appropriate MDQ for that lower-level design problem For example, an upper layer may optimize the actuator type for the particular application (e.g., hydraulic, dc, induction, stepper; see Chapter 7) with an appropriate MDQ The next lower level may optimize the motor selection (e.g., select a motor from an available set of dc motors) with another MDQ
In this manner, a complex design optimization may be achieved through several design optimizations at different design levels The nal design may not be precisely optimal, yet intuitively adequate for practical purposes; say in a conceptual design
1.4.3 Design Evolution
Traditionally, the online monitoring of responses/outputs of a system may be used to detect and diagnose the faults and malfunctions (existing or impending) of a system We believe that such monitoring may also be used to improve the design of an existing mecha-tronic system In particular, just like how a health monitoring system can pinpoint a defec-tive component in a system, it should be possible for the same system to at least identify the possible regions (sites) of design weakness in the system This is the premise of the approach for “design evolution”, as outlined below
A model of the existing system (whose design needs to be improved) and ary computing (GP) may facilitate the approach of “evolutionary” design improvement through online monitoring A possible framework for implementing this approach is indi-cated in Figure 1.7
evolution-The relevant steps are as follows:
1 Develop a model of the existing system
2 Establish (using a machine health monitoring system and an expert system) which aspects or segments of the original system (and its model) may be modi- ed/improved using information monitored from the system These will provide
“modi able sites” for the existing system/model
Trang 403 Formulate a performance function to represent the “goodness” of the design This
The optimization scheme will gradually improve the original model of the system so as
to produce better performance (as judged by the MDQ) This will require the comparison
of the monitored response of the original system and the simulated response of the model
as it evolves (improves), with respect to the MDQ In Figure 1.7, in addition to the initial model of the system, the evolutionary computing approach, and online monitoring, we have shown an expert system as well for “intelligent” decision making associated with design/model improvement This expert system may be generated from the knowledge/expertise of the existing system, its design, and engineering know how
1.5 Evolution of Mechatronics
Mechanical engineering products and systems that employ some form of electrical neering principles and devices have been developed and used since the early part of the twentieth century These systems included the automobile, electric typewriter, aircraft, and elevator Some of the power sources used in these systems were not necessarily electri-cal, but there were batteries and/or a conversion of thermal power into electricity through
engi-System model (linear graph)
Existing mechatronic system
Expert system (engineering knowledge of system)
Design improvements
Performance function (MDQ)
Optimization scheme (GP)
Machine health monitoring system
Interface (for users, domain experts, engineers, etc.)
FIGURE 1.7
Structure of a system for evolutionary design.