Rough intervals: enhancing intervals for qualitative modeling of technical systems

  • Authors:

  • M. Rebolledo

  • Affiliations:

  • Universität Stuttgart, Institute of Industrial Automation and Software Engineering, Stuttgart, Germany

  • Venue:
  • Artificial Intelligence
  • Year:
  • 2006

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Abstract

The success of model-based industrial applications generally depends on how exactly models reproduce the behavior of the real system that they represent. However, the complexity of industrial systems makes the construction of accurate models difficult. An alternative is the qualitative description of process states, for example by means of the discretization of continuous variable spaces in intervals. In order to reach the required precision in the modeling of complex dynamic systems, interval-based representations usually produce qualitative models, which are sometimes too large for practical use. The approach introduced in this paper incorporates vague and uncertain information based on principles of the Rough Set Theory as a way of enhancing the information contents in interval-based qualitative models. The resulting models are more compact and precise than ordinary qualitative models.