This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
Abstract-- An online approach to parameter estimation problems based on binary observations is presented in this paper. This recursive identification method relies on a least-mean ...
In this paper we present a novel algorithm to identify LPV systems with affine parameter dependence operating under open and closed-loop conditions. A factorization is introduced w...
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural network and genetic...
This paper is concerned with the optimal control of linear discrete-time systems, which are subject to unknown but bounded state disturbances and mixed constraints on the state an...
Paul J. Goulart, Eric C. Kerrigan, Jan M. Maciejow...