Uncertainty in control problems: A survey

Randa Herzallah*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


Plant complexity inevitably leads to poor models that exhibit a high degree of parametric or functional uncertainty. The situation becomes even more complex if the plant to be controlled is characterized by multi-valued function or even if it exhibits a number of modes of behavior during its operation. Recently, control engineers and theorist have developed new control techniques under the framework of intelligent control to enhance the performance of the controller for more complex and uncertain plants. Basically, those techniques are based on incorporating models uncertainty which are proven to give more accurate control results under uncertain conditions. in this paper we survey some approaches that appear to be promising for enhancing the performance of intelligent control systems in the face of higher level of complexity and uncertainty.

Original languageEnglish
Pages (from-to)82-90
Number of pages9
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Issue number1
Publication statusPublished - 2005


  • Adaptive control
  • Bayesian methods
  • Conditional distributions
  • Mixture density network
  • Multiple model approaches
  • Neural networks
  • Uncertainty


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