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Mechatronic Systems and Process Automation Model-Driven Approach and Practical Design Guidelines by Patrick Kaltjob | PDF Free Download.
Patrick Kaltjob has been an associate professor of electrical engineering and telecommunications at Ecole Polytechnique, UY1 since 2005. After pursuing a degree in undergraduate engineering programs at Laval and McGill (BScEng, 1996),
He received graduate degrees from the University of Wisconsin–Madison (MSc, 1999, Ph.D., 2003). He was a project investigator at Werkzeugmachinenlabor (WZL) RWTH-Aachen University, Germany (2004). His interests cover distributed control systems, smart grid, and biomedical systems.
Since 2003, he has been a senior engineering consultant for industrial processes and automation solution integrators and for global corporations operating in various industrial sectors, including cement production, electric power networks, and oil refineries.
He is an author of numerous journal articles and conference proceedings.
The high level of efficiency requirements in the design of automated systems has led to the development of new applications, including functionally integrated systems such as mechatronics and operationally integrated processes.
Such applications have proven to significantly enhance product consistency, quality, and operating safety, as well as the productivity and safety of industrial processes.
Due to their behavioristic similarities, mechatronic systems, and automated processes are usually designed by combining their time-driven and event-driven characteristics within a hybrid control scheme integrating sequential logic control with feedback control strategies and eventually with data acquisition and remote operation monitoring capabilities.
However, the current engineering literature on the design of process automation and mechatronic systems usually presents discrete-event and discrete-time systems separately, rather than in a practical integrated approach.
Challenges in the development of this unique approach are (1) the model-driven design of automation systems and processes,
(2) the integration of automation field devices and equipment through a data acquisition and communication network that is compliant with performance constraints, and (3) the incorporation of low-level regulatory control with high-level supervisory control functions.
This book is intended to revisit the design concept of process automation and mechatronic systems.
By reviewing the theoretical and practical knowledge of time-driven and event-driven systems, it offers an integrated approach and a general design methodology for the modeling, analysis,
automation, control, networking, monitoring, and sensing of various systems and processes, from single electrical-driven machines to large-scale industrial processes.
Furthermore, it covers design applications for several engineering disciplines (mechanical, manufacturing, chemical, electrical, computer, and biomedical) through real-life mechatronics design problems (e.g., hybrid vehicle, driverless car, newborn incubator, and elevator motion)
And industrial process automation case studies (e.g., power grid, wind generator, crude oil distillation, brewery bottle filling, and beer fermentation).
Through this book, the reader should acquire methods for (1) model formulation, analysis, and auditing of the single electrical-driven machine and multivariable process operations;
(2) model-driven design of software and hardware required for machine control and process automation; (3) selection and configuration of automation system field buses and network protocols;
(4) sizing and selection of electrical-driven actuating systems (including electric motors), along with their commonly used electro transmission elements and binary actuators; (5) selection and calibration of devices for process variable measurement and detection, as well as compliant data acquisition and computer interface; and (6) design of a process operation monitoring and fault management system.
Hence, the book is organized into six chapters. Chapter 1 gives a brief conceptual definition and classification of electrical driven systems and technical processes.
Functional decomposition of the automation system architecture is presented, along with some examples to illustrate automation system components for sensing, actuating, computing, signal conditioning, and communicating.
Furthermore, the generic structure of electromechanical systems with embedded automation function (i.e., mechatronics) is described, along with the interconnection structure of synchronized electromechanical systems (i.e., process automation).
Generic design requirements for process automation are outlined, and major steps of design projects in industrial automation are covered.
The integration of electric actuating systems (alternating current, direct current, and stepper motors; control valves; heaters; solenoids; etc.) with mechanical (e.g., belts and screw wheels), fluidic (pumps), or thermal transmission elements enables us to drive actions related to the dynamics of solid, liquid, and gas material or chemical reactions.
In Chapter 2, classical dynamics models for electrical-driven actuating systems are presented, along with their associated transmission element dynamics.
For each type of motor, the starting and operating conditions are derived, along with the technical specifications, suitable speed control strategies, and computer interface requirements.
Then, the resulting dynamical models for all the subcomponents are combined to derive the entire process model.
Similarly, binary actuators, such as electroactive polymers, piezo actuators, shape alloys, solenoids, and even nanodevices, are technically described and modeled.
Eventually, a motor selection and sizing procedure based on various characteristics (e.g., motion profile, load torque, and operational conditions) are presented.
In Chapter 3, models of discrete-event process operations are derived through Boolean functions, by using sequential or combinatorial logic-based techniques to capture the relationship between the state outputs of process operations and the state inputs of their transition conditions.
Hence, a logic controller design methodology for process operations (discrete-event systems) is described, from the process description and its functional analysis to formal modeling techniques, such as truth tables and K-maps, sequence table analysis and switching theory, state diagrams (Mealy and Moore), or even state function charts.
In addition, logic controller implementation strategies using sequential logic circuit design methods, such as hardwired relay network (even solid-state logic devices), μController, programmable logic controller, digital signal processing, and even field-programmable gate array, are presented.
Furthermore, some programming languages of industrial logic controllers, such as ladder diagrams, structured text, state functional charts (SFCs), instruction lists, and function blocks, are outlined.
The sketching of typical wiring diagrams related to the documentation of an automation project is discussed, along with some design strategies, such as fail-safe design and interlocks. Eventually, illustrative examples covering key logic controller design steps are presented,
From process schematics and involved input/output (I/O) equipment listings to state transition tables, I/O Boolean functions, and timing diagrams.
Examples of industrial process automation include breweries, traffic management, fruit packaging, cement portico scratchers, wood band saws, seaport gantry cranes, elevators, and car parking.
Overall, the chapter covers (1) the modeling methodology of discrete-event processes with single and multiple concurrent or mutually exclusive operating cycles, and (2) the logic controller design methodology to derive I/O Boolean functions based on truth tables and Karnaugh maps, switching theory or state diagrams,
logic programming languages, wiring, and electrical diagrams, and piping and instrumentation, and process flow diagrams.
Chapter 4 presents a generic design and implementation methodology for process monitoring and fault management combining control strategies (logic and feedback) with supervisory algorithms to ensure safe operations within discrete-event industrial processes.
First, functional and operational process requirements are used to define process control and supervision systems with respect to process data gathering, as well as process data analysis and reporting.
Subsequently, some components of the supervision and control architecture are presented, such as (1) database structure, (2) data acquisition, and (3) monitoring and decision support units. Then, the formal modeling of fault management strategies is outlined in terms of fault classification and diagnosis, as well as the integration of control strategies.
This design methodology enables the characterization of the monitoring system through the formulation of process tasks from their operational boundaries, data-type definition, and visual encoding and interaction techniques.
Some industrial cases illustrate the design of process monitoring and fault management systems (e.g., cement puzzolana drying process, brewery bottle washing process, or induction motors).
Eventually, based on cooperative requirements, a distributed control design approach to synchronize the process operations of interconnected subprocess components is described. It is illustrated through a variety of industrial applications,
such as voltage control electrical power grids or distributed manufacturing control. Overall, chapter topics include process data collection, supervisory control and data acquisition (SCADA), process data reporting, distributed control system design,
failure detection and prevention, process FAST and SADT decomposition methods, process start and stop operating mode graphical analysis, SFCs, and fault-tolerant processes.
Chapter 5 describes a spectrum of digital and analog sensing and detecting methods, as well as the technical characteristics of devices commonly encountered in industrial automation processes.
Among sensors presented, there are motion sensors (position, distance, velocity and acceleration, and flow), force sensors, pressure or torque sensors, noncontact and contact temperature sensors and detectors, proximity sensors, light sensors, and smart sensors.
The following sensing methods are covered: resistive, optoelectric, Hall effect, variable reluctance, piezoresistive, capacitive, piezoelectric, strain gauge, photoresistor, photodiode, ultrasonic, phototransistor,
triangulation, measuring wheel, radar, echelon, capacitive and inductive proximity, thermistor (NPC and PTC), infrared radiation, the rmodiode, and thermocouple. Binary detectors, such as noncontact and contact detectors (e.g., capacitive proximity, pressure switches, and vacuum switches,
radiofrequency identification (RFID)–based tracking and detection, or electromechanical contact [switch]), are described. In addition, some smart sensors based on electrostatic, piezoresistive, piezoelectric, and electromagnetic sensing principles are presented.
Furthermore, interfaces for logic-level I/O devices are described, including multiplexers, filters, and converters (digital-to-analog and analog-to-digital), using various conversion techniques (i.e., successive approximation,
dual-slope analog to digital converter (ADC), delta-encoded ADC, etc.). The sizing and selection procedures of measurement and detecting devices are accordingly presented. Then, data acquisition unit operations are described, with an emphasis on data gathering,
logging, and processing from the bus structure toward the computing unit. A selection methodology of the sample period is also outlined. Overall, chapter topics include some measurement devices of process variables (e.g., force, speed, position, pH, temperature, pressure, and gas and liquid chemical content),
RFID detection, signal conversion, sensor characteristics (resolution, accuracy, range, etc.), computer control interface, signal conditioning, data logging and processing, converters, and smart sensors.
Chapter 6 presents a review of industrial data communication networks applied to process automation with their technical characteristics, such as bus architectures and topologies, communication techniques and protocols, media, address decoding, transmission rate, and interrupt interfacing.
Among the industrial communication network protocols covered are Profibus, WordFIP, Hart, 4-20mA, and Modbus. Furthermore, the audit and benchmarking of industrial networks through performance modeling are presented, especially in terms of (1) network transmission latency,
(2) congestion rate, (3) throughput, (4) network utilization, and (5) data losses and efficiency. Hence, a generic procedure is developed for the sizing and selection, and performance evaluation of communicating protocols and cabling equipment is proposed.
Overall, chapter topics include quality of service for industrial networks, transmission component systems, transmission delay evaluation modeling, real-time information of industrial processes via the SCADA system, and actuating system remote control.
This textbook emphasizes the analysis of the real-life industrial environment and the integration of process automation system components through the suitable sizing, selection, and tuning of actuating, sensing, transmitting, and computing or controlling units.
It allows self-study via comprehensive and straightforward step-by-step modular procedures. As such, the reader is expected, at the conclusion of the textbook, to have fully mastered (1) the design requirements and design methodology for process automation systems,
(2) the sizing and selection of an industrial data transmission network and protocols, (3) the sizing and selection of the devices involved in industrial process data acquisition, and (4) the sizing and selection of actuating equipment for industrial processes.
Examples and industrial case studies are used to illustrate formal modeling, hybrid controller design, data acquisition devices selection, and transmission network architecture sizing for various types of processes.
This book was conceived to develop the reader’s skills for engineering-based problem solving, engineering system design, critical analysis, and automation system implementation. Suggested teaching plans are as follows:
(1) Chapters 1, 3, and 5 for mechatronic students with computer hardware and software programming experience; (2) all chapters, specifically Section 4.4 of Chapter 4, for advanced automation and process control students with control theory background;
(3) Chapters 1, 2, and 6 for electric machines and instrumentation students with computer hardware and software programming experience; and (4) Chapters 1, 2, 4 (specifically Section 4.4), 5, and 6 for automation field engineers aiming to design or migrate process automation systems.
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