2.3 Ways of Integration

Figure 2.3 shows a general scheme of a classical mechanical-electronic system. Such systems resulted from adding available sensors, actuators, and analog or digital controllers to mechanical components. The limits of this approach were given by the lack of suitable sensors and actuators, the unsatisfactory life time under rough operating conditions (acceleration, temperature, contamination), the large space require-ments, the required cables, and relatively slow data processing. With increasing improvements in minia-turization, robustness, and computing power of microelectronic components, one can now put more emphasis on electronics in the design of a mechatronic system. More autonomous systems can be envisioned, such as capsuled units with touchless signal transfer or bus connections, and robust microelectronics.

The integration within a mechatronic system can be performed through the integration of components and through the integration of information processing.

Integration of Components (Hardware)

The integration of components (hardware integration) results from designing the mechatronic system as an overall system and imbedding the sensors, actuators, and microcomputers into the mechanical process, as seen in Fig. 2.4. This spatial integration may be limited to the process and sensor, or to the process and actuator. Microcomputers can be integrated with the actuator, the process or sensor, or can be arranged at several places.

Integrated sensors and microcomputers lead to smart sensors, and integrated actuators and microcom-puters lead to smart actuators. For larger systems, bus connections will replace cables. Hence, there are several possibilities to build up an integrated overall system by proper integration of the hardware.

Integration of Information Processing (Software)

The integration of information processing (software integration) is mostly based on advanced control functions. Besides a basic feedforward and feedback control, an additional influence may take place through the process knowledge and corresponding online information processing, as seen in Fig. 2.4. This means a processing of available signals at higher levels, including the solution of tasks like supervision

Figure 2.4 Ways of integration within mechatronic systems.

with fault diagnosis, optimization, and general process management. The respective problem solutions result in real-time algorithms which must be adapted to the mechanical process properties, expressed by mathematical models in the form of static characteristics, or differential equations. Therefore, a knowledge base is required, comprising methods for design and information gaining, process models, and perfor-mance criteria. In this way, the mechanical parts are governed in various ways through higher level information processing with intelligent properties, possibly including learning, thus forming an integra-tion by process-adapted software.

2.4 Information Processing Systems (Basic Architecture and hw/sw Trade-offs)

The governing of mechanical systems is usually performed through actuators for the changing of posi-tions, speeds, flows, forces, torques, and voltages. The directly measurable output quantities are frequently positions, speeds, accelerations, forces, and currents.

Multilevel Control Architecture

The information processing of direct measurable input and output signals can be organized in several levels, as compared in Fig. 2.5.

level 1: low level control (feedforward, feedback for damping, stabilization, linearization)

level 2: high level control (advanced feedback control strategies)

level 3: supervision, including fault diagnosis

level 4:optimization, coordination (of processes)

level 5: general process management

Recent approaches to mechatronic systems use signal processing in the lower levels, such as damping, control of motions, or simple supervision. Digital information processing, however, allows for the solution of many tasks, like adaptive control, learning control, supervision with fault diagnosis, decisions