The BDFM as a generator in wind turbines

The Brushless Doubly-Fed Machine (BDFM) is attractive for use in wind turbines, especially offshore, as it offers high reliability by virtue of the absence of brushgear. Critical issues in the use of the BDFM in this role at a system level include the appropriate mode of operation, the sizing of associated converter and the control of the machine. At a machine level, the design of the machine and the determination of its ratings are important. Both system and machine issues are reviewed in the light of recent advances in the study of the BDFM, and preliminary comparisons are made with the well-established doubly fed wound rotor induction generator. © 2006 IEEE.

Robust filtering and smoothing with gaussian processes

We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models. GPs are gaining increasing importance in signal processing, machine learning, robotics, and control for representing unknown system functions by posterior probability distributions. This modern way of system identification is more robust than finding point estimates of a parametric function representation. Our principled filtering/smoothing approach for GP dynamic systems is based on analytic moment matching in the context of the forward-backward algorithm. Our numerical evaluations demonstrate the robustness of the proposed approach in situations where other state-of-the-art Gaussian filters and smoothers can fail. © 2011 IEEE.