Evolved finite state controller for hybrid system in reduced search space

Jean-Francois Dupuis; Zhun Fan

doi:10.1109/AIM.2009.5229908

Evolved finite state controller for hybrid system in reduced search space

Jean-Francois Dupuis, Zhun Fan

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Abstract

This paper presents an evolutionary methodology to automatically generate finite state automata (FSA) controllers to control hybrid systems. The proposed approach reduces the search space using an invariant analysis of the system. FSA controllers for a case study of two-tank system have been successfully obtained using the proposed evolutionary approach. Experimental results show that these controllers have good performance on the set of training targets as well as on a randomly generated set of validation targets.

Original language	English
Title of host publication	IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2009. AIM 2009.
Publisher	IEEE
Publication date	2009
ISBN (Print)	978-1-4244-2852-6
DOIs	https://doi.org/10.1109/AIM.2009.5229908
Publication status	Published - 2009
Event	2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics - Singapore, Singapore Duration: 14 Jul 2009 → 17 Jul 2009 https://ieeexplore.ieee.org/xpl/conhome/5211950/proceeding

Conference

Conference	2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
Country/Territory	Singapore
City	Singapore
Period	14/07/2009 → 17/07/2009
Internet address	https://ieeexplore.ieee.org/xpl/conhome/5211950/proceeding

Bibliographical note

Copyright: 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

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10.1109/AIM.2009.5229908

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title = "Evolved finite state controller for hybrid system in reduced search space",

abstract = "This paper presents an evolutionary methodology to automatically generate finite state automata (FSA) controllers to control hybrid systems. The proposed approach reduces the search space using an invariant analysis of the system. FSA controllers for a case study of two-tank system have been successfully obtained using the proposed evolutionary approach. Experimental results show that these controllers have good performance on the set of training targets as well as on a randomly generated set of validation targets.",

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Evolved finite state controller for hybrid system in reduced search space

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