Browsing by Author "Laroussi, K."

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    Fuzzy logic approach applied to the surge detection and isolation in centrifugal compressor
    (2010) Hafaifa, A.; Laaouad, F.; Laroussi, K.
    The gas compressor plants are bodies sensitive to accidental defects, the consequences of these defects on good operation of the gas pipeline can be critical. This paper presents an application of the fuzzy approach in fault detection and isolation of surge in this compression system. This paper illustrates an alternative implementation to the compression systems supervision task using the basic principles of model based fault detection and isolation associated with fuzzy modelling approach. Application results of a fault detection and isolation for a compression system are provided, which illustrate the relevance of the proposed fuzzy fault detection and isolation method. This work is con sidered a first step in accessing the factors that affect the success or limitations of surge detection and isolation in natural gas pipeline compressors
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    Implementation of a fuzzy logic system to tune a PI controller applied to an induction motor
    (2009) Laroussi, K.; Zelmat, M.; Rouff, M.
    The simplicity of traditional regulators makes them popular and the most used solution in the nowadays industry. However, they suffer from some limitations and cannot deal with nonlinear dynamics and system parameters variation. In the literature, several strategies of adaptation are developed to alleviate these limitations. In this paper, we propose a combination of two strategies for PI parameters supervision and adaptation. We apply the obtained structure to the control of induction machine speed. Simulation and experimental results of the proposed schema show good performances as compared to two strategies
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    A nonlinear model for a turbo compressor using fuzzy logic approach
    (2007) Laaouad, F.; Hafaifa, A.; Laroussi, K.
    During the last decade, significant change of direction in the development of control theory and its application has attracted great attention from the academic and industrial communities. The concept of "Intelligent Control "has been suggested as an alternative approach to conventional control techniques for complex control systems. The objective is to introduce new mechanisms permitting a more flexible control, but especially more robust one, able to deal with model uncertainties and parameter variations. In this work, we examine and illustrate the use of fuzzy logic in modelling and control design of a turbo compressor system. Turbo compressor systems are crucial part of most chemical and petrochemical plants. It's a system being very complex by its physical structure as well as its behaviour (surge problem .) The turbo compressor is considered as a complex system where many modelling and controlling efforts have been made. In the regard to the complexity and the strong non linearity of the turbo compressor dynamics, and the attempt to find a model structure which can capture in some appropriate sense the key of the dynamical properties of the physical plant, we propose to study the application possibilities of the recent control approaches and evaluate their contribution in the practical and theoretical fields consequently. Facing to the studied industrial process complexity, we choose to make recourse to fuzzy logic for analysis and treatment of its control problem owing to the fact that these technique constitute the only framework in which the types of imperfect knowledge can jointly be treated (uncertainties, inaccuracies, ...) offering suitable tools to characterise them. In the particular case of the turbo compressor, these imperfections are interpreted by modelling errors, the neglected dynamics and the parametric variations . Fuzzy logic intervene efficiently in the compressor modelling. The fuzzy logic model suggested in this work reproduced well the main characteristics of the turbo compressor dynamic model developed by Gretzer and Moore and give place to a more precise and easy to handle representation. It is about a inaccuracies reproducing with a certain degree of satisfaction of the real process without being as much complex