Literature DB >> 19884087

State-feedback control of fuzzy discrete-event systems.

Feng Lin1, Hao Ying.   

Abstract

In a 2002 paper, we combined fuzzy logic with discrete-event systems (DESs) and established an automaton model of fuzzy DESs (FDESs). The model can effectively represent deterministic uncertainties and vagueness, as well as human subjective observation and judgment inherent to many real-world problems, particularly those in biomedicine. We also investigated optimal control of FDESs and applied the results to optimize HIV/AIDS treatments for individual patients. Since then, other researchers have investigated supervisory control problems in FDESs, and several results have been obtained. These results are mostly derived by extending the traditional supervisory control of (crisp) DESs, which are string based. In this paper, we develop state-feedback control of FDESs that is different from the supervisory control extensions. We use state space to describe the system behaviors and use state feedback in control. Both disablement and enforcement are allowed. Furthermore, we study controllability based on the state space and prove that a controller exists if and only if the controlled system behavior is (state-based) controllable. We discuss various properties of the state-based controllability. Aside from novelty, the proposed new framework has the advantages of being able to address a wide range of practical problems that cannot be effectively dealt with by existing approaches. We use the diabetes treatment as an example to illustrate some key aspects of our theoretical results.

Entities:  

Mesh:

Year:  2009        PMID: 19884087      PMCID: PMC3932535          DOI: 10.1109/TSMCB.2009.2030785

Source DB:  PubMed          Journal:  IEEE Trans Syst Man Cybern B Cybern        ISSN: 1083-4419


  7 in total

1.  Supervisory control of fuzzy discrete event systems.

Authors:  Yongzhi Cao; Mingsheng Ying
Journal:  IEEE Trans Syst Man Cybern B Cybern       Date:  2005-04

2.  State-based control of fuzzy discrete-event systems.

Authors:  Yongzhi Cao; Mingsheng Ying; Guoqing Chen
Journal:  IEEE Trans Syst Man Cybern B Cybern       Date:  2007-04

3.  Supervisory control of fuzzy discrete event systems: a formal approach.

Authors:  Daowen Qiu
Journal:  IEEE Trans Syst Man Cybern B Cybern       Date:  2005-02

4.  Decision Making in Fuzzy Discrete Event Systems1.

Authors:  F Lin; H Ying; R D Macarthur; J A Cohn; D Barth-Jones; L R Crane
Journal:  Inf Sci (N Y)       Date:  2007-09-15       Impact factor: 6.795

5.  A fuzzy discrete event system approach to determining optimal HIV/AIDS treatment regimens.

Authors:  Hao Ying; Feng Lin; Rodger D MacArthur; Jonathan A Cohn; Daniel C Barth-Jones; Hong Ye; Lawrence R Crane
Journal:  IEEE Trans Inf Technol Biomed       Date:  2006-10

6.  Modeling and control of fuzzy discrete event systems.

Authors:  Feng Lin; Hao Ying
Journal:  IEEE Trans Syst Man Cybern B Cybern       Date:  2002

7.  A self-learning fuzzy discrete event system for HIV/AIDS treatment regimen selection.

Authors:  Hao Ying; Feng Lin; Rodger D MacArthur; Jonathan A Cohn; Daniel C Barth-Jones; Hong Ye; Lawrence R Crane
Journal:  IEEE Trans Syst Man Cybern B Cybern       Date:  2007-08
  7 in total
  1 in total

1.  An Error Compensation Method for Improving the Properties of a Digital Henon Map Based on the Generalized Mean Value Theorem of Differentiation.

Authors:  Yashuang Deng; Yuhui Shi
Journal:  Entropy (Basel)       Date:  2021-12-02       Impact factor: 2.524

  1 in total

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