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The control of mechatronic systems and electrical-driven processes aims to provide tools to ensure their operating performance in terms of productivity, optimization, reliability, safety, continuous operations and even stability. This is usually achieved through hybrid control paradigms using digital or analog tools. Nowadays, digital tools are widely considered to implement control systems as they offer numerous advantages including their ability: (i) to ease the control system implementation; (ii) to design complex and built-in intelligent information processing combining multiple functions for control, fault detection and diagnostic, monitoring and planning decisions; (iii) to integrate logic and continuous control algorithms as well as supervision programs into hybrid control strategies; (iv) to enhance the synchronization of input and output process operations; (v) to coordinate control actions among geographically distributed systems and processes and (iv) to achieve reliable and optimal operating conditions.

The digital control system architecture usually consists of the integration of the following functional units: a data processing and computing unit, an electrical-driven actuating unit, a measuring and detecting unit, a data acquisition (DAQ) and transmitting unit and a signal conditioning unit. The data processing and computing unit can be implemented through devices such as microcontroller (μC), programmable logic controller (PLC) with a control function, digital signal processing (DSP)a and a field-programmable gate array (FPGA).

The design of efficient control systems requires the mathematical modeling of mechatronic systems and process dynamics. This can be achieved in accordance with the operating characteristics (discrete and continuous) and objectives as well as technological constraints of the related instrumentation (signal conversion, transmission, conditioning, measurement, actuation etc.). However, in most of the current engineering literature on the design of digital control systems, the mathematical foundation of discrete time and discrete event systems is usually presented separately from the technological constraints of control instrumentation. For example, the operating time delay models or signal to noise ratio from digital device interfaces are not usually considered. Hence, the theoretical control algorithms proposed have limited practical applicability.

Challenges in the development of a practical design approach for the control of mechatronic systems and electrical-driven processes are: (i) to size and select control instrumentation in accordance with controlled system design objectives; (ii) to develop accordingly the mathematical discrete hybrid model capturing their continuous and discrete event behavioristic characteristics and (iii) to integrate the control systems with respect to technological constraints and operational characterization (discrete and continuous) (e.g. time delays, signal to noise ratios etc.).

This book intends to revisit the design concept for the control of mechatronic systems and electrical-driven processes along with the selection of control instrumentation. By reviewing the theory on discrete-time and discrete event systems as well as various elements of control instrumentation, it offers an integrated approach for: (i) the modeling and the analysis of mechatronic systems dynamics and electrical-driven process operations; (ii) the selection of actuating, sensing and conversion devices and (iii) the design of various controllers for single to multiple function electrical-driven products (mechatronic systems) and processes. Furthermore, it covers some design applications from several engineering disciplines (mechanical, manufacturing, chemical, electrical, computer, biomedical) through real-life digital control system design problems (e.g. a driverless vehicle, newborn incubator, elevator motion) and industrial process control case studies (e.g. a power grid, wind generator, crude oil distillation, brewery bottle filling, beer fermentation).

Through this book, the reader should gain methods for: (i) model formulation, analysis and auditing of single to multiple function electrical-driven products and processes; (ii) model-driven design of software and hardware required for digital control instrumentation; (iii) sizing and selection of electrical-driven actuating systems (including electric motors) along with their commonly used electro-transmission elements and binary actuators; (iv) selection and calibration of devices for process variable measurement and computer interfaces and (v) modeling, operating and integrating a wide variety of sensors and actuators. Hence, the textbook is organized into eight chapters.

1 Introduction to control of mechatronic systems. Chapter 1 gives a brief conceptual definition and classification of mechatronic systems, electrical-driven technical processes and control systems structure. Here, a functional decomposition of the generic control system architecture is presented along with some examples to illustrate control instrumentation for sensing, actuating, computing, signal converting and conditioning. Furthermore, typical functions of generic controlled system for electromechanical product and processes are described along with the interconnection between the control instrumentation. Generic requirements for control systems design are outlined based on challenges to software-based control system integration (design of hybrid architecture) and hardware-based control system integration (instrumentation sizing, compliance and selection). This is summarized within a list of major steps of control design projects.

2 Physics-based system and process dynamics modeling. Chapter 2 presents numerous examples of dynamics modeling for various electrical-driven systems and processes including transportation systems (e.g. a sea port gantry crane, hybrid vehicle, Segway, elevator, driverless car), production systems and processes (e.g. an energy-based wind turbine, drilling machine, cement based pozzolana scratcher), chemical processes (e.g. oil distillation, cake conveyor oven, city water treatment, fermentation, poultry scalding and defeathering), fluidic and thermal systems and processes (mixing tank, purified water distribution, conveyor oven, poultry scalding and defeathering thermal process) or biomedical systems (e.g. infant incubator, human blood glucose insulin metabolism). Systems and process behaviors can be captured through differential equations using an experimental data modeling approach and classical physical laws of conservation and continuity. The resulting models are capable of displaying multiple and nonlinear variables as well as time variant parameter characteristics that can further be simplified according to the system physical properties or operating boundaries. A methodology for physics-based modeling is presented through the deterministic or stochastic behavior models of commonly encountered electrical-driven systems and large-scale processes. A review on linear modeling methods such as stochastic, dynamics response or state space is presented in the Appendices.

3 Discrete time system modeling and signal conversion methods. Chapter 3 focuses on methods to derive discrete approximation of continuous systems and signals using tools, such as the hold equivalent, pole-zero mapping, numerical integration and z-transformation theorems. A technological description of computer control architecture and interface is proposed with respect to DAQ unit operations from the bus structure to data gathering, logging and processing with respect to signal noise reduction and approximation consideration. Critical issues related to signal conversion, such as aliasing effects, along with the methodology for selection of sample period are also covered. A selection methodology of the sample period is also outlined. Overall, the chapter topics include technology and methods for continuous signal digital conversion and reconstruction such as bilinear transformation, discrete-time command sequence generation, computer control interface for data logging, conditioning and processing, sample time selection and computer conversion technology using various conversion techniques (i.e. successive approximation, dual slope ADC, delta-encoded ADC, etc.), as well as processing delay effects.

4 Discrete time analysis methods. Chapter 4 presents methods related to discrete system dynamical analysis in the frequency and time domains. Moreover, stability definition and tests for discrete time system are discussed and controlled system performance assessment tools are outlined. This chapter aims to present discrete controller design specifications. Chapter topics include frequency analysis tools such as (DTFT, FFT, DFT), discrete zero and pole location plots, stability tests and criterion for discrete time systems (Jury–Marden test, Routh–Hurwitz), steady-state error, performance indices (ITAE, ISE), time and frequency properties for controller design (settling time, percentage overshoot, gain and phase margins).

5 Continuous digital controller design. Chapter 5 presents various approaches to design the PID controller algorithms, such as continuous time design, discrete design and direct design using roots-locus, and frequency response techniques as well as some advanced techniques, such as model predictive control. Hence, using time or frequency domain controller specifications, numerous examples of designing and tuning control algorithms are described ranging from PID family, deadbeat, feedforward and cascade, to non-interacting control algorithms. In addition to stability analysis tests, performance indices and dynamics response analysis are derived in frequency and time domains. Furthermore, the open loop controller design for stepper motors as well as scalar and vector control design for induction motors are described. Model predictive control algorithms suitable for process operations with physical, safety and performance constraints are also presented. Eventually, comparative analyses between classical PID controllers with various state feedback topologies for DC motor speed control are performed. Overall, chapter topics include cascade control, design and tuning methods for discrete-time classical PID family controllers, scalar and vector control. The digital state feedback controller concept is revisited for cases where it is not possible to measure all state variables. Comparatively, analyses between classical PID controllers and various state feedback topologies for DC motor speed control are presented.

6 Logic controller design. Chapter 6 presents Boolean function-based models that have been derived by using sequential or combinatorial logic-based techniques to capture the relationship between the state outputs of discrete event system operations and the state inputs of their transition conditions. Hence, after performing process description and functional analysis, a design methodology of a logic controller for process operations (discrete event systems) is proposed. Subsequent systems behavioristic formal modeling is achieved by using techniques such as truth table and K-maps, sequence table analysis and switching theory, state diagram (Mealy and Moore) or even state function charts. Some illustrative examples covering key logic controller design steps are presented from process schematics and involved I/O equipment listing, wiring diagrams with some design strategies such as fail-safe design and interlocks, to state transition tables, I/O Boolean function and timing diagrams. Examples of logic controller designs include cases of elevator vertical transportation, an automatic fruit picker, a driverless car and biomedical systems such as robot surgery and laser-based surgery. Overall, the chapter topics cover: (i) the methodology for Boolean algebra based on the modeling of discrete event systems and (ii) logic controller design methodology to derive input/output (I/O) Boolean functions based on truth table and Karnaugh maps, switching theory or state diagrams, wiring and electrical diagrams and P&I and PF diagrams.

7 Hybrid process controller design. Chapter 7 presents a generic design and implementation methodology for process monitoring and control strategies (logic and continuous) with algorithms to ensure operations safety of hybrid systems (i.e. systems integrating discrete event and discrete time characteristics). First, functional and operational process requirements are outlined to define hybrid control and supervision systems with respect to logic and continuous control software and data integration and process data gathering as well as multi-functional process data analysis and reporting. Subsequently, a design methodology is proposed for the design of monitoring and control systems. Some cases are used to illustrate the design of process monitoring and hybrid control for elevator motion, drying cement pozzolana and a brewery bottle washing process. Overall, chapter topics include hybrid control system design, piping and instrumentation diagram, system operations FAST and SADT decomposition methods, process start and stop operating mode graphical analysis and a sequential functional chart (SFC) as well as process interlock design.

8 Instrumentation modeling: sensors, detectors and electrical-driven actuators. Chapter 8 provides an overview of electrical-driven actuators models and sensors encountered in mechatronics with their technical specifications and performance requirements. This is suitable for electric motors, electrofluidic and electrothermal actuating systems. Similarly, binary actuators such as electroactive polymers, piezo-actuators, shape alloys, solenoids and even nano devices are technically described and modeled. In addition, Chapter 8 describes a spectrum of digital and analog sensing and detecting methods as well as the technical characterization and physical operating principles of the instrumentation commonly encountered in mechatronic systems. Among sensors presented, there are motion sensors (position, distance, velocity, flow and acceleration), force sensors, pressure or torque sensors (contact-free and contact) temperature sensors and detectors, proximity sensors, light sensors and smart sensors, capacitive proximity, pressure switches and vacuum switches, RFID-based tracking devices and electromechanical contact switches. In addition, some smart sensing instrumentation based on electrostatic, piezo-resistive, piezo-electric and electromagnetic sensing principles are presented. Overall, chapter topics include actuating systems such as motors (AC, DC and stepper), belt, screw-wheels, pumps, heaters and valves along with detection and measurement devices of process variables (force, speed, position, temperature, pressure, gas and liquid chemical content), RFID detection, sensor characteristics (resolution, accuracy, range etc.) and nano as well as smart sensors.

This textbook emphases on the modeling and analysis of real-life environment and the integration of control design and instrumentation components of mechatronic systems through a suitable selection and tuning of actuating, sensing, transmitting and computing or controlling units. Indeed, this book covers control instrumentation such as sensors, transducers and actuators as well as aspects of matching and interconnecting these control instruments, particularly the interface between connected devices and signal conversion, modification and conditioning. As such, the reader is expected at the conclusion of this textbook to have fully mastered: (i) the design requirements and the design methodology for control systems; (ii) the sizing and selection of the instrumentation involved in industrial process control as well as microelectromechanical devices and smart sensors; (iii) the use of microprocessors for process control, as well as signal conditioning and (iv) the sizing and the selection of actuating equipment for industrial processes. Numerous examples and case studies are used to illustrate formal modeling, hybrid controller design and the selection of instrumentation for electrical-driven machine actuation and DAQ related to systems dynamics and process operations. Through these case studies, the reader should gain practical understanding of topics related to the control system and instrumentation allowing him/her to fulfill a control and instrument engineering position where he/she is expected: (i) to possess a good knowledge of instrumentation operating conditions and control requirements; (ii) to size and select control instrumentation; (iii) to design, develop and implement digital controllers; (iv) to design engineering processes and electrical-driven systems; (v) to collaborate with design engineers and process engineers and technicians for the cost- and time-based acquisition of systems and processes control equipment and (vi) to perform technical audit to ensure instruments compliance with health and safety regulations.

This book is conceived to develop the reader's skills for engineering-based problem solving, engineering system design, critical analysis and implementation of control systems and instrumentation. It allows self-study via comprehensive and straightforward step-by-step modular procedures. In addition, examples with their accompanying MATLAB^® routines, as well as design and selection related exercises and problems, are provided with their solutions. Furthermore, a dedicated textbook companion website allows the reader to download additional material for teaching, such as slide presentations of the chapter material, data files for additional laboratory sessions, example files as well as 2D and 3D innovative virtual labs of physical real-life systems (i.e. model-based simulation tools that could be associated to real life system for in-class lab sessions).

Suggestions for a teaching plan for applied control theory of mechatronic systems and electrical-driven processes would be as follows: (i) Chapter 1 through Chapter 5 (up to Section 5.3.1) for an introductory digital control level course during a semester; (ii) Chapters 2, 3 and 5 (Sections 5.3 and 5.4) for advanced control students with a control theory background; (iii) Chapters 1, 3 (Sections 3.3 and 3.4) and 8 for electric-driven machine and instrumentation students with computer hardware and software programming experience; (iv) Chapters 2, 3 (Sections 3.3 and 3.4), 5 (Sections 5.2.4, 5.3 and 5.4) and 6–8 for field control and instrumentation engineers interested in the design or the migration of process control of hybrid systems.