Abstract
The paper proposes a dependability model to evaluate the behavior of a CAN network in scenarios of transient faults which affect data communications. Fault occurrence is modeled by a Markov Modulated Poisson Process (MMPP) which is capable to describe the typical behavior of electromagnetic interferences (EMI) that occur in industrial environments. An accurate and efficient representation of the network behavior is achieved by adopting a set of assumptions that reduce the pessimism level and which are closer to the real operating conditions. The model is based on Stochastic Petri Nets, which are a high-level modeling formalism able to produce very compact and efficient models, supporting both analytical and simulation solutions. Dependability measures are established from the fulfillment of the real-time constraints (deadlines) defined on messages exchanged between network nodes. Analytical and simulation solutions are both investigated. A case study is proposed to asses both model performance and network dependability. Copyright © 2005 IFAC.

Abstract
This paper describes a simulation model for a multi-legged locomotion system with joints at the legs having viscous friction, flexibility and backlash. For that objective the robot prescribed motion is characterized in terms of several locomotion variables. Moreover, the robot body is divided into several segments in order to emulate the behaviour of an animal spine. The foot-ground interaction is modelled through a non-linear spring-dashpot system whose parameters are extracted from the studies on soil mechanics. To conclude, the performance of the developed simulation model is evaluated through a set of experiments while the robot leg joints are controlled using fractional order algorithms.

Abstract
The objective of this paper is to present novel control strategies for MicroGrid operation, especially in islanded mode. The control strategies involve mainly the coordination of secondary load-frequency control by a MicroGrid Central Controller that heads a hierarchical control system able to assure stable and secure operation when the islanding of the MicroGrid occurs and in load-following situations in islanded mode.

Abstract
The need to generate random wave fields with a pre-determined spectrum is a common one. One of the typical applications requiring this capability is the need to interface spectral and deterministic models. The spectra and integral parameters produced as output of spectral models must often be transformed into wave fields which can be used as input to deterministic models (e.g. Navier-Stokes based numerical models). Also, the instantaneous statistics of the produced wave field must be controlled. This is typically the case when the objective is to evaluate the influence of these statistics in the appearance of certain wave phenomena. In this article we propose a parametric based approach to the wave field generation. Not only is this a computationally efficient way of generating local elevation sequences, but it also enables perfect control of both the instantaneous and spectral characteristics of the generated waves. Two examples of applications will be given. One, where the developed generator will be used to investigate the influence of the spectral model and the instantaneous statistics of the wave field in extreme wave generation. A second example will be the generation of a boundary field for a Navier-Stokes based model starting from the spectral output of the SWAM model.

Abstract
Industrial control systems architectures have been evolving to the decentralization of control tasks. This evolution associated with the time-critical nature Of these tasks, increases the dependability requirements for one of their most critical components: the communication system. Therefore, this is an important aspect on the control system design which must be properly evaluated. In this paper the dependability of a PROFIBUS network is assessed. By using of a fault injection framework the network operation is disturbed with fault scenarios which are representative of industrial environments. From these experiments, the stability of the PROFIBUS logical ring is analyzed, the main outages causes are identified and their probabilities are obtained.

Abstract
Fuzzy modelling has been widely applied as a powerful methodology for the identification of nonlinear systems from process measurements. Most applications use flat sets of fuzzy rules, which are hardly interpretable black-box approaches. Hierarchical modelling is a promising tool to deal with real world complex systems. A large-scale model can be easily readable if it is partitioned into several independent smaller models to represent functional relations of the processes involved in the system. This article deals with the application of a new fuzzy modelling technique that automatically organizes the sets of fuzzy IF-THEN rules in a Hierarchical Collaborative Structure. This organizational structure makes the fuzzy model interpretable as in the case of the physical model. This new methodology was tested to split the inside greenhouse air temperature and humidity flat fuzzy models into fuzzy sub-models. which have alike counterpart on the physical sub-models.