Intelligent Systems (Basic Tasks)

Introduction:

The information processing within mechatronic systems may range between simple control functions and intelligent control. Various definitions of intelligent control systems do exist.

 

Intelligent Systems (Basic Tasks)

 An intelligent control system may be organized as an online expert system, and comprises

1.       multi-control functions (executive functions),

2.       A knowledge base,

3.       Inference mechanisms, and

4.       Communication interfaces.

The online control functions are usually organized in multilevel the knowledge base contains quantitative and qualitative knowledge.

The quantitative part operates with analytic (mathematical) 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., possibility 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”, 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 loads (learning), supervises all relevant.

Elements, and performs a fault diagnosis (supervision) to request maintenance or, if a failure occurs, to request a failsafe 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.