Optimal experiment designs with respect to the intended model application
Automatica (Journal of IFAC)
For model-based control design, closed-loop identification gives better performance
Automatica (Journal of IFAC)
Identification for control: Optimal input intended to identify a minimum variance controller
Automatica (Journal of IFAC)
Brief Some results on optimal experiment design
Automatica (Journal of IFAC)
From experiment design to closed-loop control
Automatica (Journal of IFAC)
| Hi-index | 22.14 |
It is well known that if we intend to use a minimum variance control strategy, which is designed based on a model obtained from an identification experiment, the best experiment which can be performed on the system to determine such a model (subject to output power constraints, or for some specific model structures) is to use the true minimum variance controller. This result has been derived under several circumstances, first using asymptotic (in model order) variance expressions but also more recently for ARMAX models of finite order. In this paper we re-approach this problem using a recently developed expression for the variance of parametric frequency function estimates. This allows a geometric analysis of the problem and the generalization of the aforementioned finite model order ARMAX results to general linear model structures.