Control of Mechatronic Systems: Model-Driven Design and Implementation Guidelines

A practical methodology for designing integrated automation control for systems and processes Implementing digital control within mechanical-electronic (mechatronic) systems is essential to respond to the growing demand for high-efficiency machines and processes. In practice, the most efficient digital control often integrates time-driven and event-driven characteristics within a single control scheme. However, most of the current engineering literature on the design of digital control systems presents discrete-time systems and discrete-event systems separately. Control Of Mechatronic Systems: Model-Driven Design And Implementation Guidelines unites the two systems, revisiting the concept of automated control by presenting a unique practical methodology for whole-system integration. With its innovative hybrid approach to the modeling, analysis, and design of control systems, this text provides material for mechatronic engineering and process automation courses, as well as for self-study across engineering disciplines. Real-life design problems and automation case studies help readers transfer theory to practice, whether they are building single machines or large-scale industrial systems.  Presents a novel approach to the integration of discrete-time and discrete-event systems within mechatronic systems and industrial processes Offers user-friendly self-study units, with worked examples and numerous real-world exercises in each chapter Covers a range of engineering disciplines and applies to small- and large-scale systems, for broad appeal in research and practice Provides a firm theoretical foundation allowing readers to comprehend the underlying technologies of mechatronic systems and processes  Control Of Mechatronic Systems is an important text for advanced students and professionals of all levels engaged in a broad range of engineering disciplines.

Table of Contents:
Preface xiii Acknowledgment xix About the Companion Website xxi 1 Introduction to the Control of Mechatronic Systems 1 1.1 Introduction 1 1.2 Description of Mechatronic Systems 1 1.3 Generic Controlled Mechatronic System and Instrumentation Components 6 1.3.1 The Data Processing and Computing Unit 6 1.3.2 Data Acquisition and Transmission Units 7 1.3.3 Electrically-driven Actuating Units 7 1.3.4 Measuring and Detecting Units 7 1.3.5 Signal Conditioning Units 7 1.4 Functions and Examples of Controlled Mechatronic Systems and Processes 8 1.5 Controller Design Integration Steps and Implementation Strategies 9 Exercises and Problems 16 Bibliography 26 2 Physics-Based Systems and Processes: Dynamics Modeling 27 2.1 Introduction 27 2.2 Generic Dynamic Modeling Methodology 27 2.3 Transportation Systems and Processes 28 2.3.1 Sea Gantry Crane Handling Process 28 2.3.1.1 Model 1 33 2.3.1.2 Model 2 33 2.3.2 Vertical Elevator System 35 2.3.3 Hybrid Vehicle Powertrain with Parallel Configuration 38 2.3.3.1 Motor Driving and Regenerating Model 40 2.3.3.2 Vehicle Gear Box Model 41 2.3.3.3 Brake System Model 41 2.3.4 Driverless Vehicle Longitudinal Dynamics 42 2.3.5 Automated Segway Transportation Systems 45 2.4 Biomedical Systems and Processes 47 2.4.1 Infant Incubator 47 2.4.2 Blood Glucose-Insulin Metabolism 50 2.5 Fluidic and Thermal Systems and Processes 53 2.5.1 Mixing Tank 53 2.5.2 Purified Water Distribution Process 57 2.5.3 Conveyor Cake Oven 60 2.5.4 Poultry Scalding and Defeathering Thermal Process 64 2.6 Chemical Processes 68 2.6.1 Crude Oil Distillation Petrochemical Process 68 2.6.2 Lager Beer Fermentation Tank 73 2.7 Production Systems and Processes 75 2.7.1 Single Axis Drilling System 75 2.7.2 Cement-Based Pozzolana Portal Scraper 78 2.7.3 Variable Pitch Wind Turbine Generator System 81 Exercises and Problems 84 Bibliography 102 3 Discrete-Time Modeling and Conversion Methods 105 3.1 Introduction 105 3.2 Digital Signal Processing Preliminaries 105 3.2.1 Digital Signal Characterization 105 3.2.2 Difference Equation: Discrete-Time Signal Characterization Using Approximation Methods 109 3.2.2.1 Numerical Approximation Using Forward Difference 109 3.2.2.2 Numerical Equivalence Using Backward Difference 110 3.2.2.3 Numerical Equivalence Using Bilinear Transform 110 3.2.3 Z-Transform and Inverse Z-Transform: Theorems and Properties 117 3.2.4 Procedure for Discrete-Time Approximation of the Continuous Process Model 119 3.2.4.1 Z-Transfer Functions and Block Diagram Manipulation 119 3.2.5 Conversion and Reconstruction of the Continuous Signal: Sampling and Hold Device 124 3.2.5.1 Sampler and Hold-Based Process Model 124 3.2.5.2 Construction Methods of a Continuous Signal from a Data Sequence 127 3.3 Signal Conditioning 135 3.4 Signal Conversion Technology 137 3.4.1 Digital-to-Analog Conversion 137 3.4.2 Analog-to-Digital Conversion 140 3.5 Data Logging and Processing 145 3.5.1 Computer Bus Structure and Applications 145 3.6 Computer Interface and Data Sampling Issues 149 3.6.1 Signal Conversion Time Delay Effects 155 3.6.1.1 Nyquist Sampling Theorem and Shannon’s Interpolation Formula 156 3.6.2 Estimation of the Minimum Sampling Rate to Be Selected 157 3.6.2.1 Remarks on Sample Periods 160 Exercises and Problems 161 Bibliography 168 4 Discrete-Time Analysis Methods 169 4.1 Introduction 169 4.2 Analysis Tools of Discrete-Time Systems and Processes 169 4.2.1 Discrete Pole and Zero Location 169 4.2.2 Discrete Frequency Analysis Tools: Fourier Series and Transform (DFT, DTFT, and FFT) 176 4.2.2.1 Discrete System Frequency Response 178 4.2.2.2 Sketching Procedure for the Frequency Response of a Discrete System 179 4.2.2.3 Properties of a Frequency Response 179 4.3 Discrete-Time Controller Specifications 181 4.3.1 Time Domain Specifications 182 4.3.2 Frequency Response Specifications 184 4.4 Discrete-Time Steady-State Error Analysis 186 4.5 Stability Test for Discrete-Time Systems 187 4.5.1 Bound-Input Bound-Output (BIBO) Stability Definition 188 4.5.2 Zero-Input Stability Definition 188 4.5.3 Bilinear Transformation and the Routh–Hurwitz Criterion 188 4.5.4 Jury–Marden Stability Test 190 4.5.5 Frequency-Based Stability Analysis 191 4.6 Performance Indices and System Dynamical Analysis 191 Exercises and Problems 192 Bibliography 194 5 Continuous Digital Controller Design 197 5.1 Introduction 197 5.2 Design of Control Algorithms for Continuous Systems and Processes 197 5.2.1 Direct Design Controller Algorithms 199 5.2.2 Discrete PID Controller Algorithms 201 5.2.2.1 Proportional Control Algorithm 201 5.2.2.2 Derivative Control Algorithm 202 5.2.2.3 Integral Control Algorithm 202 5.2.2.4 PI Control Algorithm 202 5.2.2.5 PD Control Algorithm 202 5.2.2.6 Classical PID Controller Algorithm 202 5.2.2.7 Properties of and Some Remarks on PID Controller Algorithms 204 5.2.3 PID Controller Gains Design Using a Frequency Response Technique 205 5.2.3.1 Design Procedure for PID Controller Design 205 5.2.4 PID Controller Gains Design Using a Root Locus Technique 220 5.2.4.1 Design Procedures 221 5.2.5 Feedforward Control Methods 226 5.2.5.1 Command Input Feedforward Control Algorithm 226 5.2.5.2 Disturbance Feedforward Control Algorithm 234 5.3 Modern Control Topologies 235 5.3.1 State Feedback PID Control Algorithms 235 5.3.2 MPC Algorithms 246 5.3.3 Open-Loop Position Control Using SteppingMotors 249 5.4 Induction Motor Controller Design 252 5.4.1 Scalar Control (V/f Control) 252 5.4.1.1 Open-Loop Scalar Control 253 5.4.1.2 Closed-Loop Scalar Control (Slip Control) 253 5.4.2 Vector Control 253 5.4.2.1 Direct Torque Control 254 5.4.2.2 Speed Control of AC Motors 256 5.4.2.3 Speed Control of DC Motors 257 Exercises and Problems 259 Bibliography 281 6 Boolean-Based Modeling and Logic Controller Design 283 6.1 Introduction 283 6.2 Generic Boolean-Based Modeling Methodology 284 6.2.1 System Operation Description and Functional Analysis 284 6.2.2 Combinatorial and Sequential Logic Systems 288 6.2.2.1 Combinational Modeling Tools: Truth Table, SOP, Product of Sums (POS), K-Maps 289 6.2.2.2 Sequential Modeling Tools: Sequence Table, Switching Theory, and State Diagram 290 6.3 Production Systems 297 6.3.1 Portico Scratcher 297 6.4 Biomedical Systems 299 6.4.1 Robot-Assisted Surgery 299 6.4.2 Laser Surgery Devices 303 6.5 Transportation Systems 307 6.5.1 Elevator Motion Systems 307 6.5.2 Fruit-Picker Arm 311 6.5.3 Driverless Car 313 6.6 Fail-Safe Design and Interlock Issues 317 6.6.1 Logic Control Validation (Commissioning) 317 Exercises and Problems 318 Bibliography 336 7 Hybrid Controller Design 337 7.1 Introduction 337 7.2 Requirements for Monitoring and Control of Hybrid Systems 337 7.2.1 Requirements for Hybrid Control System Design 338 7.2.2 Requirements for Operations Monitoring System Design 338 7.2.3 Process Interlock Design Requirements 339 7.3 Design Methodology for Monitoring and Control Systems 340 7.4 Examples of Hybrid Control and Case Studies 347 7.4.1 Elevator Motion System 347 7.4.2 Bottle-Cleaning Process 350 7.4.3 Cement-Drying Process 352 Exercises and Problems 362 Bibliography 375 8 Mechatronics Instrumentation: Actuators and Sensors 377 8.1 Introduction 377 8.2 Actuators in Mechatronics 378 8.3 Electromechanical Actuating Systems 379 8.3.1 Solenoids 379 8.3.2 Digital Binary Actuators 381 8.3.3 DC Motors 382 8.3.4 AC Motors 387 8.3.5 Stepping Motors 389 8.3.6 Transmission Mechanical Variables 390 8.4 Electro-Fluidic Actuating Systems 393 8.4.1 Electric Motorized Pumps 393 8.4.2 Electric-Driven Cylinders 395 8.4.3 Electrovalves 396 8.5 Electrothermal Actuating Systems 398 8.6 Sensors in Mechatronics 400 8.6.1 Measurement Instruments 402 8.6.1.1 Relative Position (Distance) 402 8.6.1.2 Angular Position Measurement Using an Encoder and a Resolver 409 8.6.1.3 Velocity Measurement 412 8.6.1.4 Acceleration Measurement 414 8.6.1.5 Force Measurement 416 8.6.1.6 Torque Measurement 417 8.6.1.7 Flow Measurement 417 8.6.1.8 Pressure Measurement 419 8.6.1.9 Liquid-Level Measurement 420 8.6.1.10 Radio Frequency-Based Level Measurement 422 8.6.1.11 Smart and Nano Sensors 422 8.6.2 Detection Instruments 423 8.6.2.1 Electromechanical Limit Switches 424 8.6.2.2 Photoelectric Sensors 424 8.6.2.3 RFID-Based Tracking and Detection 424 8.6.2.4 Binary Devices: Pressure Switches and Vacuum Switches 426 Exercises and Problems 426 Bibliography 434 A Stochastic Modeling 437 A.1 Discrete Process Model State-Space Form 437 A.2 Auto-Regressive Model with an eXogenous Input: ARX Model Structure 438 A.3 The Auto-Regressive Model – AR Model Structure 438 A.4 The Moving Average Model – MA Model Structure 438 A.5 The Auto-Regressive Moving Average Model – ARMA Model Structure 439 A.6 The Auto-Regressive Moving Average with eXogenous Input Model – ARMAX Model Structure 439 A.7 Selection of Model Order and Delay 439 A.8 Parameter Estimation Methods 440 A.9 LS Estimation Methods 442 A.10 RLS Estimation Methods 443 A.11 Model Validation 443 A.12 Prediction Error Analysis Methods 444 A.13 Estimation of Confidence Intervals for Parameters 444 A.14 Checking for I/O Consistency for Different Models 445 B Step Response Modeling 447 C Z-Transform Tables 451 D Boolean Algebra, Bus Drivers, and Logic Gates 455 D.1 Some Logic Gates, Flip-Flops, and Drivers 455 D.2 Other Logic Devices: Drivers and Bus Drivers 457 D.3 Gated R − S Latch 459 D.4 D-Type (Delay-Flip-Flop) 459 D.5 Register or Buffer 461 D.6 Adder 461 E Solid-State Devices and Power Electronics 463 E.1 Power Diodes 463 E.2 Diode–Transistor Logic (DTL) 464 E.3 Power Transistors 465 E.4 Resistor–Transistor Logic (RTL) 465 E.5 Transistor–Transistor Logic (TTL) 466 E.6 Metal Oxide Semiconductor FET (MOSFET) 466 E.7 Thyristors 467 Index 469

About the Author :
Patrick O. J. Kaltjob, PhD Eng, is an associate professor of electrical engineering and telecommunications at Ecole Polytechnique, UY1, and has been a visiting researcher at WZL RWTH-Aachen, Germany. His research interests include distributed control systems, smart grids, and biomedical systems. Professor Kaltjob is also a consultant for various industrial infrastructure and technology service providers, including in the cement plant, brewery, oil refinery, and electrical power grid industries.