Name
Abstract | ||
|---|---|---|
We study the problem of globally stabilizing through measurement feedback a class of uncertain stochastic nonlinear systems in feedforward (or upper triangular) form, with state equations affected by a Wiener process adapted to a given filtration of /spl sigma/-algebras and measurements affected by a sample continuous and strongly Markov stochastic process adapted to the same filtration of /spl sigma/-algebras. We propose a step-by step design, based on splitting the system /spl Sigma/ into one-dimensional interconnected systems /spl Sigma//sub j/, j=1,...,n. Moreover, we introduce the notion of practical stability in probability, which corresponds to having a large probability of being the state small in norm whenever the noise affecting the measurements has a "small" second order moment. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/TAC.2004.841129 | IEEE Trans. Automat. Contr. |
Keywords | Field | DocType |
Stochastic systems,Nonlinear systems,Noise measurement,Nonlinear equations,Control systems,State feedback,Filtration,Stability,Measurement uncertainty,Adaptive control | Computer vision,Corner detection,Mathematical analysis,Algorithm,Ground truth,Artificial intelligence,Pixel,Probabilistic logic,Mathematics | Journal |
Volume | Issue | ISSN |
50 | 1 | 0018-9286 |
Citations | PageRank | References |
4 | 0.62 | 1 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefano Battilotti | 1 | 136 | 42.34 |