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《Acta Automatica Sinica》 2003-05
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Hybrid System Monitoring and Diagnosing Based on Particle Filter Algorithm

MO Yi-Wei XIAO De-Yun(Department of Automation, Tsinghua University, Beijing 100084)  
State estimation of hybrid system, which consists of discrete state estimation and continuous state estimation, is a critical issue in hybrid system study. Utilizing the advantage of particle filter, which can estimate the discrete and continuous states simultaneously, we propose a new approach for monitoring and diagnosing of hybrid system. After giving the derivation of algorithm and design steps, we discuss the issues arising from algorithm implementation and propose an improved algorithm. The result of simulation shows the feasibility of particle filter in hybrid system monitoring and diagnosing, and it also demonstrates that the proposed improved algorithm can achieve better result.
【Fund】: SupportedbyNationalHighTechnologyProgram(2 0 0 2AA4 12 4 2 0 )
【CateGory Index】: TP277
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