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.

Sommario

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

Info autore

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.

Riassunto

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.

Dettagli sul prodotto

• Autori: Patrick O J Kaltjob, Patrick O. J. Kaltjob, Poj Kaltjob
• Editore: Wiley, John and Sons Ltd
• Lingue: Inglese
• Formato: Copertina rigida
• Pubblicazione: 30.04.2019
• EAN: 9781119505808
• ISBN: 978-1-119-50580-8
• Pagine: 496
• Categorie: Scienze naturali, medicina, informatica, tecnica > Tecnica > Meccanica, tecnica di produzione; Maschinenbau, Mechatronik, Regelungstechnik, Systemtechnik, Mechanical Engineering, Electrical & Electronics Engineering, Elektrotechnik u. Elektronik, Systemtechnik u. -management, Systems Engineering & Management, Mess- u. Regeltechnik, Control Process & Measurements, Control Systems Technology