Abstract
This paper discusses our tool for automatic generation
of structured models for complex dynamic processes by
means of genetic programming. In contrast to other
techniques which use genetic programming to find an
appropriate arithmetic expression in order to describe
the input-output behaviour of a process, this tool is
based on a block oriented approach with a transparent
description of signal paths. A short survey on other
techniques for computer based system identification is
given and the basic concept of SMOG (Structured MOdel
Generator) is described. Furthermore latest extensions
of the system are presented in detail, including
automatic defined sub-models and qualitative fitness
criteria.
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