1 the physical layer, being either wired or wireless connection, such as twisted-pair wiring, fiber-optic cable or radio link, and the commutation unit connecting the network to the devices (e.g. field buses for data transfer between primary controllers and field control devices);
2 the network, transmission, and transport layers performing functions such as data routing over the network, data flow control, packet segmentation and desegmentation, error control and clock synchronization. In addition, these layers provide mechanisms for packet tracking and the retransmission of failed packets; and
3 the session and presentation layers mainly used for data formatting.
1.3.3 Electrically-driven Actuating Units
Electrically-driven actuating units convert voltage or current signals from the computing unit into appropriate input forms (mechanical, electrical, thermal, fluidic etc.) for the execution of machine's and process operations. Then those converted signals produce variations in the machine's physical variables (e.g. torque, heat, or flow), or amplify the energy level of the signal, causing changes in the process operation dynamics. Some examples of actuating elements are relays, magnets, and servo motors.
1.3.4 Measuring and Detecting Units
Measuring and detecting units consist of low-power devices, such as sensors and switch-based detectors interfacing with electrically-driven machines involved in process operations. As such, they convert related physical output signals from the actuating unit into voltage or binary signals ready to be used within the data processing and computing unit. Some key functions of these devices are: (i) data acquisition related to the change of machine variables; and (ii) conversion of the machine-gathered signal into electrical or optical signals. Depending on the nature of the process signal generated, a signal conditioner can be added.
1.3.5 Signal Conditioning Units
Signal conditioning elements convert the nature of the signal generated by the sensing device into another suitable signal form (usually electrical). The signal conditioning units can also be embedded within the sensing devices. An example of such a unit is a Resistance Temperature Detector (RTD). Here, a change in the temperature of its environment is converted into a voltage signal reflecting its resistance change through a Wheatstone bridge and the bridge is a signal conditioning module.
1.4 Functions and Examples of Controlled Mechatronic Systems and Processes
Mechatronic systems and processes have built-in intelligence through either their advanced information processing systems such as multifunctional control systems or intelligent electromechanical systems (including thermal, fluid, and mechanical processes) such as power-efficient multi-axis actuation with motion precision and detection features or miniaturized smart devices with embedded information processing capabilities. The resulting controlled mechatronic systems and processes aim to achieve various objectives: synchronize, control and sequence process operations, or detect and monitor process status.
Table 1.1 presents some typical process control objectives and their corresponding control functions along with some illustrative examples.
Table 1.1 Functions and implementation strategies for controlling mechatronic systems and processes.
| Control system processing functions | Implementation control strategies | Examples of controlled mechatronic systems and processes |
|---|---|---|
| Assessing, reporting, and monitoring | Recording process variables through sensors and detectors; real-time, model-based measurement, setting parameters, and input signals. | Remote power flow measurement, configuration and voltage control (SCADA) through switchgears, transformers, and condensers in a smart power grid. |
| Safety compliance, detection, and diagnostics | Interlocking in case of detected failure modes, maintaining safety operations while ensuring malfunction handling. | Integrated safety and monitoring of petrochemical process variables and parameters (flowrate, temperature etc.) |
| Control and performance enhancement | Controlling or regulating system variables. | Position and temperature measurement as well as control of a 2D cutting machinery process. |
Example 1.3
Robot-assisted surgery is using image-guided systems to command and control operations in intravascular surgery, as depicted in Figure 1.6. Such a system has an embedded and integrated control system for its motion and direction, as well as operation monitoring, and motion synchronization between robot arms. Expected control functions include:
1 force control of a robot arm gripper;
2 synchronized angular position and velocity control of each motor-driven robot joint;
3 logic control of real-time anomalies detection (location of the abnormal cell or dysfunctional organ) and inspection using 3D imaging camera processing (color uniformity, selection based on size and shape) and laser ranging sensors;
4 path generation and motion planning (position, speed, and accelerations) for robot navigation while ensuring collision avoidance of the robot manipulator; and
5 logic control of the discrete selection of suitable cutting tools for the robot arms.
Figure 1.6 Image-guided tele-assisted robot intravascular surgery.
Example 1.4
An unmanned electric vehicle driving system is expected to have an embedded and integrated control system for speed and direction control, traffic light monitoring, and motion synchronization with other users. Consider the driverless vehicle in Figure 1.7(a): a block diagram with all relevant input and output (I/O) variables involved is depicted in Figure 1.7(b).
Figure 1.7 (a) Chassis of a driverless vehicle. Source: Based on Kaltjob P. (b) Hybrid control block diagram of a driverless vehicle.
Example 1.5
Here, an example of control system for a crane-based vertical motion process is illustrated in Figure 1.8, while its feedback