Abstract
This paper addresses the problem of robustly tuning power system stabilisers (PSSs) in systems with large wind power integration. PSSs installed in wind energy conversion systems, namely in doubly fed induction generators, are used in this research to provide additional damping to the electromechanical modes of oscillation. A new method that aims to reduce the computational effort required to find a robust solution that is suitable for a very large set of operating conditions is also proposed.

Abstract

Abstract
This paper focuses the control problem of a nonholonomic autonomous underwater vehicle, moving in the tridimensional space. The dynamic of a body in submarine environments is strongly nonlinear. This implies that classical linear controllers are often inadequate whereby Lyapunov theory is here considered. Methods based in this theory are promising tools to design controllers and are applied to the case of MARES, a small-sized autonomous underwater vehicle. Several controllers based only on Lyapunov theory are determined while others combine linear and nonlinear control theory in order to perform various maneuvers. Aiming to verify the correct performance of controllers, simulations and experiments are carried out.

Abstract
This paper is concerned with modeling and simulation in Matlab/Simulink of wind energy systems with different topologies for the power converters: matrix converter and multilevel converter. We use pulse modulation by space vector modulation associated with sliding mode for controlling the converters, and we introduce power factor control at the output of the converters. Finally, we present the electric behavior for the power and the current at the input and at the output of the converters.

Abstract
This paper presents a frequency offset estimation approach to ultra wide band Impulse Radio (UWB-IR) systems based upon the classical idea by Schmidl and Cox. The approach secures low complexity by exploiting the low duty cycle of the time hopping access, assures estimation robustness for all UWB-IR bands by working in the frequency domain, attains quasi optimal performances (at 0.5 dB from the Cramer Rao lower bound) by a careful settings choice, and accomplishes robustness at low signal to noise ratio by a suitable combining algorithm. Performance in a realistic IEEE 802.15.4a scenario are also provided. © 2009 IEEE.

Abstract
Binary decision trees based on univariate splits have traditionally employed so-called impurity functions as a means of searching for the best node splits. Such functions use estimates of the class distributions. In the present paper we introduce a new concept to binary tree design: instead of working with the class distributions of the data we work directly with the distribution of the errors originated by the node splits. Concretely, we search for the best splits using a minimum entropy-of-error (MEE) strategy. This strategy has recently been applied in other areas (e.g. regression, clustering, blind source separation, neural network training) with success. We show that MEE trees are capable of producing good results with often simpler trees, have interesting generalization properties and in the many experiments we have performed they could be used without pruning.