Publications Scientifiques

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End date: 2009Subject: search.filters.subject.Fuzzy logic

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Now showing 1 - 9 of 9
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    Fuzzy logic-based controller for position regulation of electric drives
    (Advances in Modelling and Analysis C, 2007) Chermalikh, A.V.; Chetate, Boukhmis; Maidanski, I.I.; Kheldoum, A.
    Electrical drives are characterized by their natural non- linearity owing to their proper design and their time-varying mathematical models. When used to drive industrial systems, e.g. variable speed or variable position drives, conventional control methods are usually applied to design speed and position controllers. However, at certain performance level, these methods are not satisfied. The present paper combines fuzzy logic, mostly used to control system characterized by non-linearity and uncertainty, with new control structures to overcome difficulties listed earlier. The obtained results have proved the good foundation of the suggested method
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    Fuzzy control motion design for mobile robots in unknown environments
    (2009) Hachour, O.
    we present an algorithm for path planning to a target for mobile robot in unknown environment. The proposed algorithm allows a mobile robot to navigate through static obstacles, and finding the path in order to reach the target without collision. This algorithm provides the robot the possibility to move from the initial position to the final position (target). The proposed path finding strategy is designed in a grid-map form of an unknown environment with static unknown obstacles. The robot moves within the unknown environment by sensing and avoiding the obstacles coming across its way towards the target. When the mission is executed, it is necessary to plan an optimal or feasible path for itself avoiding obstructions in its way and minimizing a cost such as time, energy, and distance. In order to get an intelligent component, the use of Fuzzy Logic In order to get an intelligent component, the use of Fuzzy Logic (FL), and Expert Systems (ES) is necessary to bring the behavior of Intelligent Autonomous Vehicles (IAV). To present a real intelligent task and to deal with autonomy requirements such as power and thermal, (FL), and Expert Systems (ES) is necessary to bring the behavior of Intelligent Autonomous Vehicles (IAV). The aim work must make the robot able to achieve these tasks: to avoid obstacles, and to make ones way toward its target by ES-FL system capturing the behavior of a human expert. The integration of ES and FL has proven to be a way to develop useful realworld applications, and hybrid systems involving robust adaptive control. The proposed approach has the advantage of being generic and can be changed at the user demand. The results are satisfactory to see the great number of environments treated. The results are satisfactory and promising
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    Fuzzy logic controller for a pneumatic artificial muscle robot based on sliding mode control
    (2009) Rezoug, Abdellah; Meddahi, A.; Baizid, K.; Hamerlain, m.; Tadjine, M.
    Fuzzy Logic Control (FLC) has been successfully established in control systems engineering in the recent years, in other hand, Sliding Mode Control (SMC) is an active area in control research. The combination of this tow fields called Fuzzy Sliding Mode Control (FSMC) techniques to exploit the superior sides of these two controllers have drawn the attention of the scientific community. In this work, we proposed fuzzy logic controller based on the sliding mode theory to control the robot arm actuated by the pneumatics artificial muscles. Using bang-bang motion generation law, the objective of the control is the position and the velocity tracking by the robot. Simulations results demonstrate the feasibility and the advantages of our proposed research work.
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    Fuzzy clustering for finding fuzzy partitions of many-valued attribute domains in a concept analysis perspective
    (2009) Djouadi, Y.; Alouane, Basma; Prade, H.
    Although an overall knowledge discovery process consists of a distinct pre-processing stage followed by the data mining step, it seems that existing formal concept analysis (FCA) and association rules mining (ARM) approaches, dealing with many-valued contexts, mainly focus on the data mining stage. An "intelligent" pre-processing of input contexts is often absent in existing FCA/ARM approaches, leading to an unavoidable information loss. Usually, many-valued attribute domains need to be first fuzzily partitioned. However, it is unrealistic that the most appropriate fuzzy partitions can be provided by domain experts. In this paper, an unsupervised learning stage, based on Fuzzy C-Means algorithm, is proposed in order to get fuzzy partitions that are faithful to data for quantitative attribute domains, and consequently for avoiding the loss of valuable association rules due to the use of empirical fuzzy partitions. More precisely, the paper reports an experiment where it is shown that some rules are no longer found because their support or confidence is too low when using such empirical partitions. Experimental results show that the learned fuzzy partition outperforms human expert fuzzy partitions. More generally, the paper provide discussions about the handling of many-valued attributes in both fuzzy FCA and fuzzy ARM
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    Nonlinear sensitive control of centrifugal compressor
    (2007) Laaouad, F.; Bouguerra, M.; Hafaifa, A.; Iratni, A.
    In this work, we treat the problems related to chemical and petrochemical plants of a certain complex process taking the centrifugal compressor as an example, a system being very complex by its physical structure as well as its behaviour (surge phenomenon). We propose to study the application possibilities of the recent control approaches to the compressor behaviour, and consequently evaluate their contribution in the practical and theoretical fields. Facing 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 techniques constitute the only framework in which the types of imperfect knowledge can jointly be treated (uncertainties, inaccuracies, etc..) offering suitable tools to characterise them. In the particular case of the centrifugal compressor, these imperfections are interpreted by modelling errors, the neglected dynamics, no modelisable dynamics and the parametric variations. The purpose of this paper is to produce a total robust nonlinear controller design method to stabilize the compression process at its optimum steady state by manipulating the gas rate flow. In order to cope with both the parameter uncertainty and the structured non linearity of the plant, the proposed method consists of a linear steady state regulation that ensures robust optimal control and of a nonlinear compensation that achieves the exact input/output linearization
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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
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    A method of minimizing the power losses in an induction motor with a squirrel-cage with vector control
    (2004) Chetate, Boukhmis; Kheldoun, Aissa
    An approach to optimizing the flux linkage of the rotor of an induction motor is considered when the motor operates in a vector control mode with indirect orientation in the direction of the field. In this system, the expression for the frequency of the rotor e.m.f. contains the rotor winding impedance; this impedance must therefore be precisely estimated in real time. It is proposed that this should be done using a fuzzy-logic adaptation mechanism. The results of using such a mechanism in a physical model confirm its effectiveness. Key words: induction motor, rotor, vector control, fuzzy logic
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    A combined IQG/LTR and fuzzy logic strategy for the improved control of a drum-type boiler-turbine plant
    (2009) Habbi, H.; Kidouche, M.; Zelmat, M.
    This paper addresses the design of a fuzzy control system with a fuzzy controller and a fuzzy estimator for a fossil-fuelled drum-type boiler-turbine unit. The fuzzy control method is based on a dynamic Takagi-Sugeno (TS) fuzzy model which has been developed in Habbi et al. [Automatica 39 (2003) 1213] for the nonlinear steam power plant. In the design procedure, a dynamics augmentation is first suggested and a dynamic fuzzy augmented system is determined to deal with the non-minimum phase behaviour of the plant. The global fuzzy control system is designed from a local concept viewpoint using the optimal control theory. To assess the performance of the proposed optimal fuzzy controller, simulations under various operation conditions including actuators saturation are performed over a wide operating range of the physical plant