JSM 2005 - Toronto

Abstract #303797

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 476
Type: Topic Contributed
Date/Time: Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #303797
Title: Identification and Adaptive Control of ARX Models with Occasional Parameter Jumps via Fast Particle Filters
Author(s): Yuguo Chen*+
Companies: Duke University
Address: Box 90251 Duke University, Durham, NC, 27708-0251, United States
Keywords: Importance sampling ; Resampling ; Adaptive control ; ARX models with parameter jumps
Abstract:

By proper choice of proposal distributions for importance sampling and of resampling schemes for sequentially updating the importance weights, this talk address the problem of online identification and adaptive control of ARX models with occasional parameter jumps by using fast particle filters that can be implemented online via parallel recursions. Theoretical analysis and simulation studies show improvements of this new approach over conventional methods.

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Revised March 2005