Showing papers by "Michel Gevers published in 1996"
TL;DR: It is shown that, when the controller is a smooth function of the input-output dynamics and the disturbance spectrum, the best controller performance is achieved by performing the identification in closed loop with an operating controller that is the ideal controller.
261 citations
TL;DR: In this paper, a conceptual characterization of the various ways of addressing the problem of identification for control is presented, which leads to distinguish between a dual control approach, an optimal experiment design approach and a robust control approach.
73 citations
TL;DR: Using singular value decomposition (SVD) techniques, it is shown that in noise undermodeling situations, the remaining data may introduce large bias on the model parameters with a possible increase of their total mean square error.
Abstract: We present results concerning the parameter estimates obtained by prediction error methods in the case of input that are insufficiently rich. Such input signals are typical of industrial measurements where occasional stepwise reference changes occur. As is intuitively obvious, the data located around the input signal discontinuities carry most of the useful information. Using singular value decomposition (SVD) techniques, we show that in noise undermodeling situations, the remaining data may introduce large bias on the model parameters with a possible increase of their total mean square error. A data selection criterion is then proposed to discard such poorly informative data to increase the accuracy of the transfer function estimate. The system discussed in particular is a SISO ARMAX system.
21 citations
11 Dec 1996
TL;DR: Using the dual Youla parametrizations of controller-based coprime factor plant perturbations and plant-based PCF controller perturbation, the authors characterize the set of all plants that have the same optimal LQG or MV controller.
Abstract: Using the dual Youla parametrizations of controller-based coprime factor plant perturbations and plant-based coprime factor controller perturbations, we characterize the set of all plants that have the same optimal LQG or MV controller.
2 citations