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EN
In this contribution, a control scheme based on multi input multi output Fuzzy Sliding Mode control (MIMOFSMC) for linear speed regulation of multi-motors system is proposed. Once the decoupled model of the multi- motors system is obtained, a smooth control function with a threshold was chosen to indicate how far the state from to the sliding surface is. However, the magnitude of this control function depends closely on the upper bound of uncertainties, and this generates chattering. So, this magnitude has to be chosen with great care to obtain high performances. Usually the upper bound of uncertainties is difficult to known before motor operation, so, a Fuzzy Sliding Mode controller is investigated to solve this difficulty; a simple Fuzzy inference mechanism is used to reduce the chattering phenomenon by simple adjustments. A simulation study is carried out and shows that the proposed controller has great potential for use as an alternative to the conventional sliding mode contro.
EN
Web winding systems allow the operations of unwinding and rewinding of various products including plastic films, sheets of paper, sheets, and fabrics. These operations are necessary for the development and the treatment of these products. Web winding systems generally consist of the same machine elements in spite of the diversity of the transported products. Due to the wide rang variation of the radius and inertia of the rollers the system dynamic change considerably during the winding/ unwinding process. Decentralized PI controller for web tension control and linear speed control are presented in this paper. The PI control method can be applied easily and is widely known, it has an important place in control applications. Simulation results show the effectiveness of the proposed linear speed and tension controller for web winding multi motors systems.
EN
Sliding mode and fuzzy logic control have been combined together in a variety of ways. In this paper, a novel direction to design fuzzy sliding controllers is proposed based on the approach of Ben-Ghalia et al. Which is able to provide a fuzzy set based on a decoupled and linear system obtained after the application of the feedback- linearization control to the model of an induction motor. On the other hand, a Luenberger observer is conceived in the present work to observe the rotor flux in the motor which is too important to permit the application of fuzzy modeling approach and ensure the optimal and required performances . Furthermore, another objective to use such an observer consists in stabilizing the system and rejecting the disturbances when the system is subjected to uncertainties. Furthermore, to overcome the problem of the chattering phenomenon generated by the application of conventional sliding mode control applied to the cascade structure of the motor, the approach of fuzzy sliding mode control based on the fuzzy modelling proposed by Ben-Ghalia is used. The robust fuzzy control design is made feasible without resorting to model simplification or imposing restrictive conditions on the system uncertainty. Finally, simulation results proves the capability of the proposed process to ensure a good performances and robustness which is the principal aim of this research
EN
In this paper, a new approach of linguistic fuzzy modeling proposed by Ben-Ghalia et al. is applied to induction motor. Thus, a classical model is first given together with the most used asynchronous motor control strategy, which is the pole assignment. After more, in order to minimize the dependence of the system to parameter variations and external perturbations, and reduce the number of variable states, a new model of the original system is proposed. This model is too simple and is suitable to cognitive approach such as fuzzy modeling. Then, fuzzy modeling of an uncertain system using the approach of Ben-Ghalia et al. to reduce the effects of imperfections of the classical modeling are introduced. In addition, their applications in the fuzzy sliding mode control of the asynchronous motor are presented. Finally, Simulation results reveal some very interesting features and show that the proposed fuzzy model has great potential for use as an alternative to the approximation of the conventional model of induction motor taking into account the effect of system model uncertainties and gives a good performances in sliding mode control.
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