Name
Abstract | ||
|---|---|---|
Iterative data-based controller tuning consists of iterative adjustment of the controller parameters towards the parameter values which minimise an H2 performance criterion. The convergence to the global minimum of the performance criterion depends on the initial controller parameters and on the step size of each iteration. This article presents convergence properties of iterative algorithms when they are affected by disturbances. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1080/00207721.2011.563874 | Int. J. Systems Science |
Keywords | Field | DocType |
parameter value,convergence property,controller parameter,steepest descent method,iterative data-based controller tuning,iterative adjustment,h2 performance criterion,performance criterion,robust convergence,initial controller parameter,iterative algorithm,global minimum,robust estimator,nonlinear programming,stochastic approximation | Convergence (routing),Mathematical optimization,Control theory,Method of steepest descent,Control theory,Nonlinear programming,Stochastic approximation,Mathematics | Journal |
Volume | Issue | ISSN |
43 | 10 | 0020-7721 |
Citations | PageRank | References |
4 | 0.46 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Diego Eckhard | 1 | 17 | 3.57 |
| AlexandreSanfelice Bazanella | 2 | 4 | 0.46 |