Name
Title | ||
|---|---|---|
Identification and Adaptive Control of Change-Point ARX Models Via Rao-Blackwellized Particle Filters |
Abstract | ||
|---|---|---|
By proper choice of proposal distributions for importance sampling and of resampling schemes for sequentially updating the importance weights, we address the problem of on-line identification and adaptive control of autoregressive models with exogenous inputs (ARX models) with Markov parameter jumps. Particle filters that can be implemented online via parallel recursions are developed by making use of explicit formulas of the posterior means of the time-varying parameters. Theoretical analysis and simulation studies show improvements of this approach over conventional methods |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TAC.2006.887913 | IEEE Trans. Automat. Contr. |
Keywords | Field | DocType |
Adaptive control,Particle filters,Monte Carlo methods,Hidden Markov models,Statistics,Proposals,Analytical models,Surges,Nonlinear filters,Random number generation | Importance sampling,Markov process,Control theory,Markov model,Particle filter,Markov chain,Adaptive control,System identification,Resampling,Mathematics | Journal |
Volume | Issue | ISSN |
52 | 1 | 0018-9286 |
Citations | PageRank | References |
1 | 0.40 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuguo Chen | 1 | 187 | 11.67 |
| Tze Leung Lai | 2 | 89 | 15.87 |