Name
Title | ||
|---|---|---|
Self-tuning control based on generalized minimum variance criterion for auto-regressive models |
Abstract | ||
|---|---|---|
Theoretical problems on self-tuning control include stability, performance and convergence of the recursive algorithm involved. In this paper, the problem of controlling minimum or non-minimum phase auto-regressive models with constant but unknown parameters is considered. The stability of an algorithm obtained by combining a recursive estimator for the controller parameters and a generalized minimum variance criterion is proved. The main result is the theorem which assures the overall stability for the closed-loop system in presence of white noise in the input-output relation, where the estimated parameters do not necessarily converge to the true values. The algorithm is proved by the Lyapunov theory. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.automatica.2007.11.008 | Automatica |
Keywords | Field | DocType |
AR systems,Discrete-time systems,Generalized minimum variance control,Self-tuning control,Sliding mode control | Minimum-variance unbiased estimator,Lyapunov function,Control theory,Mathematical optimization,Control theory,White noise,Self-tuning,Minimum phase,Mathematics,Estimator,Sliding mode control | Journal |
Volume | Issue | ISSN |
44 | 8 | Automatica |
Citations | PageRank | References |
11 | 1.27 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anna Patete | 1 | 15 | 3.42 |
| Katsuhisa Furuta | 2 | 167 | 76.43 |
| M. Tomizuka | 3 | 1464 | 294.37 |