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

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

Research output: Contribution to journalConference article

25 Citations (Scopus)

Abstract

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)
Pages (from-to)519-524
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume1
StatePublished - Dec 1 2004
Externally publishedYes
Event2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas
Duration: Dec 14 2004Dec 17 2004

Fingerprint

Discrete Event Systems
Discrete event simulation
Planning
Cost functions
Medicine
Monotonic
Decision making
Statistics
Statistic
Cost Function
Optimal Control Problem
State Space
Optimal Control
Decision Making
Maximise
Dependent
Evaluation
Costs
Modeling

Keywords

  • 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

Cite this

Control of fuzzy discrete event systems and its applications to clinical treatment planning. / Lin, F.; Ying, H.; Luan, X.; MacArthur, Rodger David; Cohn, J. A.; Barth-Jones, D.; Crane, L. R.

In: Proceedings of the IEEE Conference on Decision and Control, Vol. 1, 01.12.2004, p. 519-524.

Research output: Contribution to journalConference article

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AU - MacArthur, Rodger David

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AU - Barth-Jones, D.

AU - Crane, L. R.

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