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
