Empirical Inference
Conference Paper
2003
Adaptive, Cautious, Predictive control with Gaussian Process Priors
PDFNonparametric Gaussian Process models, a Bayesian statistics approach, are used to implement a nonlinear adaptive control law. Predictions, including propagation of the state uncertainty are made over a k-step horizon. The expected value of a quadratic cost function is minimised, over this prediction horizon, without ignoring the variance of the model predictions. The general method and its main features are illustrated on a simulation example.
| Author(s): | Murray-Smith, R. and Sbarbaro, D. and Rasmussen, CE. and Girard, A. |
| Links: | |
| Journal: | Proceedings of the 13th IFAC Symposium on System Identification |
| Pages: | 1195-1200 |
| Year: | 2003 |
| Month: | August |
| Day: | 0 |
| Editors: | Van den Hof, P., B. Wahlberg and S. Weiland |
| BibTeX Type: | Conference Paper (inproceedings) |
| Event Name: | Proceedings of the 13th IFAC Symposium on System Identification |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
| Organization: | Max-Planck-Gesellschaft |
| School: | Biologische Kybernetik |
BibTeX
@inproceedings{2316,
title = {Adaptive, Cautious, Predictive control with Gaussian Process Priors},
journal = {Proceedings of the 13th IFAC Symposium on System Identification},
abstract = {Nonparametric Gaussian Process models, a Bayesian statistics approach, are used to implement a nonlinear adaptive control law. Predictions, including propagation of the state uncertainty are made over a k-step horizon. The expected value of a quadratic cost function is minimised, over this prediction horizon, without ignoring the variance of the model predictions. The general method and its main features are illustrated on a simulation example.},
pages = {1195-1200},
editors = {Van den Hof, P., B. Wahlberg and S. Weiland},
organization = {Max-Planck-Gesellschaft},
school = {Biologische Kybernetik},
month = aug,
year = {2003},
author = {Murray-Smith, R. and Sbarbaro, D. and Rasmussen, CE. and Girard, A.},
month_numeric = {8}
}