Page 35 - The Mechatronics Handbook

The online control functions are usually organized in multilevels, as already described. The knowledge
base contains quantitative and qualitative knowledge. The quantitative part operates with analytic (math-
ematical) process models, parameter and state estimation methods, analytic design methods (e.g., for
control and fault detection), and quantitative optimization methods. Similar modules hold for the
qualitative knowledge (e.g., in the form of rules for fuzzy and soft computing). Further knowledge is the
past history in the memory and the possibility to predict the behavior. Finally, tasks or schedules may
be included.
The inference mechanism draws conclusions either by quantitative reasoning (e.g., Boolean methods)
or by qualitative reasoning (e.g., possibilistic methods) and takes decisions for the executive functions.
Communication between the different modules, an information management database, and the man–
machine interaction has to be organized.
Based on these functions of an online expert system, an intelligent system can be built up, with the
ability “to model, reason and learn the process and its automatic functions within a given frame and to
govern it towards a certain goal.” Hence, intelligent mechatronic systems can be developed, ranging from
“low-degree intelligent” [13], such as intelligent actuators, to “fairly intelligent systems,” such as self-
navigating automatic guided vehicles.
An intelligent mechatronic system adapts the controller to the mostly nonlinear behavior (adaptation),
and stores its controller parameters in dependence on the position and load (learning), supervises all relevant
elements, and performs a fault diagnosis (supervision) to request maintenance or, if a failure occurs, to
request a fail safe action (decisions on actions). In the case of multiple components, supervision may help
to switch off the faulty component and to perform a reconfiguration of the controlled process.

2.5 Concurrent Design Procedure for Mechatronic Systems

The design of mechatronic systems requires a systematic development and use of modern design tools.

Design Steps
Table 2.3 shows five important development steps for mechatronic systems, starting from a purely
mechanical system and resulting in a fully integrated mechatronic system. Depending on the kind of
mechanical system, the intensity of the single development steps is different. For precision mechanical
devices, fairly integrated mechatronic systems do exist. The influence of the electronics on mechanical
elements may be considerable, as shown by adaptive dampers, anti-lock system brakes, and automatic
gears. However, complete machines and vehicles show first a mechatronic design of their elements, and
then slowly a redesign of parts of the overall structure as can be observed in the development of machine
tools, robots, and vehicle bodies.

Required CAD// //CAE Tools

The computer aided development of mechatronic systems comprises:
1. constructive specification in the engineering development stage using CAD and CAE tools,
2. model building for obtaining static and dynamic process models,
3. transformation into computer codes for system simulation, and
4. programming and implementation of the final mechatronic software.
Some software tools are described in [31]. A broad range of CAD/CAE tools is available for 2D- and
3D-mechanical design, such as Auto CAD with a direct link to CAM (computer-aided manufacturing),
and PADS, for multilayer, printed-circuit board layout. However, the state of computer-aided modeling
is not as advanced. Object-oriented languages such as DYMOLA and MOBILE for modeling of large
combined systems are described in [31–33]. These packages are based on specified ordinary differential

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