Abstract
This paper describes the newly developed Vector Control Signal Processing (VCSP) blockset for use with Matlab(R) and Simulink(R). The originality of this blockset consists on the extension of Simulink for design, simulation and prototyping of signal processing algorithms in motion control systems. This blockset is the first know collection of Simulink blocks to bridge the gap between digital algorithm development and subsequent implementation in motion control systems. The VCSP blockset together with Real-Time Workshop uses the inherent visual programming techniques of Simulink and a number of pre-built blocks to reach the above goals. Due to its open and flexible nature this approach is also very useful as a tool for teaching. This paper is focused on modelling and simulation of motion control systems, in particular employing rotating AC machines and vector control methods. The basic of blockset functions and some examples of modelling techniques for simple drive and complex drive structures are presented, Simulations results are also presented and discussed.

Abstract
This paper describe an instrument for real-time visualization of the quantities necessary for analysis, diagnosis and investigations of AC machine drives on an oscillographic display. The instruments needs no shaft position or speed sensor, it uses exclusively the acquired stator currents and voltages and provides information, in electrical and visual form of: stator and rotor flux, torque, reactive power, torque current, flux current, torque angle, slip frequency. The measuring instrument is based in analogue signal processing techniques. The main fields of application are: monitoring systems, control units, research tool for induction motor drives, and test shop. Practical results of the implementation are presented and discussed.

Abstract
Knowledge of the health of power transformers is important to prevent high costs caused by failures and to maintain the quality of the service. On-line monitoring and diagnosis seem to be the right way to reach this objective. In this paper a set of experiences related to the installation of vibration and temperature sensors inside a test transformer will be described. Different types of sensors have been tested, and some of them discarded because of induced electromagnetical noise. Some of the main results and conclusions are shown in this paper. These experiences are included in a more general project called TRAFES, whose main objective is the continuous monitoring and diagnosis of large power transformers.

Abstract
When inference is performed with the compositional rule of inference (CRI), fuzzy rules can be mathematically modelled by a pair of operators, the implication function and the modus ponens generating function, each pair being a possible model for the rule. Analyzing the firing condition of fuzzy rules, that is the condition the hypothesis and the observation must verify to infer a non trivial conclusion, it is possible to get a deeper understanding of the behaviour of the different models that can be used, and valuable semantical criteria can be obtained to select the best suitable model. The firing condition of any model can be expressed by means of a generalized possibility or necessity measure generated by its implication and modus ponens generating functions, measures that quantify the amount of uncertainty or possibilistic uncertainty of the conclusion. Two different types of possibility distributions can be identified as those concluded from different types of models, that is necessary and possible possibility distributions, corresponding to necessary and possible conclusions.

Abstract
This paper presents an artificial neural network (ANN) based approach for the definition of preventive control strategies of autonomous power systems with a large renewable power penetration. For a given operating point, a fast dynamic security evaluation for a specified wind perturbation is performed using an ANN. If insecurity is detected, new alternative stable operating points are suggested, using a hybrid ANN-optimization approach that checks several feasible possibilities, resulting from changes in power produced by diesel and wind generators, and other combinations of diesel units in operation, Results obtained from computer simulations of the real power system of Lemnos (Greece) support the validity of the developed approach.

Abstract
This paper presents a Monte-Carlo algorithm considering loads defined by fuzzy numbers. In this methodology states are sampled according to the probabilistic models governing the life cycle of system components while fuzzy concepts are used to model uncertainty related to future load behavior. This model can be used to evaluate generation/transmission power system reliability for long term planning studies as one uses the more adequate uncertainty models for each type of data. For each sampled state a Fuzzy Optimal Power Flow is run so that one builds its power not supplied membership function. The paper proposes new indices reflecting the integration of probabilistic models and fuzzy concepts and discusses the application of variance reduction techniques if loads are defined by fuzzy numbers. A case-study based on the IEEE 30 bus system illustrates this methodology.