@inbook{749b65ec2e6145a4a0a8ae8042c1d9e6,
title = "Fault and mode switching identification for hybrid systems with application to electro-hydraulic system in vehicles",
abstract = "This paper describes a methodology for simultaneous identification of fault parame-ters and mode switching events for hybrid systems. The method is developed based on the notion of Global Analytical Redundancy Relations (GARR) from the bond graph model of the hybrid system. A unified formula with mode change time sequence and initial mode coefficients (IMC) is derived to represent the mode switching. It employs Genetic Algorithm (GA) to search for fault parameters and mode switching time stamps. Fault parameters, mode switching time stamps and all IMC are encoded into one chromosome as a potential solution of the identification process. GARRs are used as a fitness index in GA search. An electro-hydraulic system of vehicle is studied to illustrate the efficiency of the proposed algorithm.",
author = "Ming Yu and Ming Luo and Shai Arogeti and Danwei Wang and Xinzheng Zhang",
year = "2009",
month = mar,
day = "19",
doi = "10.1007/978-3-642-00264-9_17",
language = "English",
isbn = "9783642002632",
series = "Studies in Computational Intelligence",
pages = "257--274",
editor = "Angus Budiyono and Bambang Riyanto and Endra Joelianto",
booktitle = "Intelligent Unmanned Systems",
}