Paper Info
Title
Simultaneous fault and mode switching identification for hybrid systems based on particle swarm optimization
Abstract
This paper describes a methodology for simultaneous identification of fault parameters and mode switching events for hybrid systems. The method is developed based on the notion of Global Analytical Redundancy Relations (GARRs) 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. Due to the discontinuous characteristic of the mode switching, an adaptive hybrid particle swarm optimization (AHPSO) employing the combination of real valued PSO (RPSO) and binary valued PSO (BPSO) is proposed to optimize different parts of solution simultaneously, a novel individual level adaptive method using fuzzy system is developed to dynamically adjust the algorithm parameters. GARRs are used as a fitness index of the AHPSO. Case studies of different energy domains are carried out to illustrate the efficiency of the proposed algorithm.
Year
DOI
Venue
2010
10.1016/j.eswa.2009.09.033
Expert Syst. Appl.
Keywords
Field
DocType
different part,mode change time sequence,hybrid system,fuzzy system,mode switching time stamps,novel individual level adaptive,mode switching,simultaneous fault,particle swarm optimization,fault parameter,initial mode coefficient,algorithm parameter,bond graph,global analytical redundancy relation,different energy domain,adaptive hybrid particle swarm
Particle swarm optimization,Control theory,Computer science,Mode (statistics),Multi-swarm optimization,Redundancy (engineering),Bond graph,Fuzzy control system,Hybrid system,Binary number
Journal
Volume
Issue
ISSN
37
4
Expert Systems With Applications
Citations 
PageRank 
References 
3
0.43
9
Authors
5
Name
Order
Citations
PageRank
Ming Yu1857.43
Ming Luo2272.82
Danwei Wang31529175.13
Shai Arogeti4142.42
Xinzheng Zhang5206.26