Control of fuzzy discrete event systems and its applications to clinical treatment planning

F. Lin, H. Ying, X. Luan, R. D. MacArthur, J. A. Cohn, D. Barth-Jones, L. R. Crane

Research output: Contribution to journalConference articlepeer-review

17 Scopus citations


In this paper, we further develop a modeling and control approach to fuzzy discrete event systems that we initially proposed in [LY01, LY02]. We first investigate an optimal control problem in fuzzy discrete event systems. The problem is abstracted from real applications in biomedical fields. The control objective is to maximize a treatment effectiveness measure while keeping some cost below a given level. This problem is difficult because both the effectiveness function and the cost function are state dependent and hence are not monotonic. Furthermore, the state space of a fuzzy discrete event system is infinite in general. We develop an online approach that can solve this problem. We then apply this approach to HIV/AIDS treatment planning, because it is one of the most difficult treatments in medicine. We also develop a novel computerized treatment decision-making system based on the optimal control approach. The preliminary statistic evaluation of our system shows a strong agreement between the physicians and our system in terms of which treatment regimens to be used for patients of various conditions.

Original languageEnglish (US)
Article numberTuB02.5
Pages (from-to)519-524
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 2004
Externally publishedYes
Event2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas
Duration: Dec 14 2004Dec 17 2004


  • AIDS
  • Decision-making
  • Discrete event systems
  • Fuzzy logic
  • HIV
  • Optimal control
  • Treatment planning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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