Browsing by Author "Chetate, Boukhmis"

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Adaptive control of induction machine by fuzzy logic
(2003) Chetate, Boukhmis; Kheldoun, Aissa
The effective operation of a decoupled induction machine by rotor field oriented technique is altered by the variation of rotor resistance and the operation with small loads. In fact, the variation of the rotor resistance causes an increase in the copper losses. But the operation with small loads causes excessive iron losses. The present work, present a study permitting the maintain of he driver efficiency in the case of the operations stated above . Two mechanisms are developed, first one based on the fuzzy logic, its objective is to adapt the rotor resistance, whereas the second is based on the optimization of the total losses. This mechanism permits to obtain the value of the optimal control of flux rotor, which correspond to optimal consumption of the energy. The obtained simulation results have shown a good foundation of this approach
Adaptive control of induction motor using artificial neural network with estimation of rotor flux
(2007) Chetate, Boukhmis; Kabache, Nadir; Ladiguin, Anatoly Nikolaevitch
Adaptive control of induction motor with unknown motor resistance
(2007) Chetate, Boukhmis; Bradai, Rafik; Kabache, Nadir
In this paper, a new approach for induction motor rotor resistance variation estimate is presented by using adaptive neural networks. Indeed, the proposed neural networks are endowed with adaptive rules that allow them to estimate the true values of the necessary nonlinear state feedbacks for the input-output feedback linearization control of an induction motor. A comparison between the nonlinear state feedbacks provided by neural networks and those calculated through the nominal model of the induction motor with nominal parameters allows us to estimate the variation in the rotor resistance
Adaptive fuzzy inference control of the recycle compression system
(Praise Worthy Prize, 2014) Zammoum Boushaki, Razika; Zamoum, Y.; Chetate, Boukhmis
ANN based double stator asynchronous machine diagnosis taking torque change into account
(IEEE, 2008) Khodja, Djalal Eddine; Chetate, Boukhmis
In this work the strategy of the artificial intelligence (neural networks) is used to detect and localize the defects of the double stator asynchronous machine. In fact, several neural networks have been applied to the detection of defects. Then, we used a selector which allows activating only one network at a time. In this case, the selected network detects only defects corresponding to the torque developed by asynchronous machine. Finally, the simulation results were presented to show the effectiveness of artificial neural networks for automatic fault diagnosis
Application of the neurone – fuzzy technique for the minimisation of MF of asynchronous machine fuzzy speed regulator
(2003) Bradai, Rafik; Chetate, Boukhmis
From their early discovry, the fuzzy-neural techniques did not show enough use and interest in other fields of research as it for systems identification and diagnosis. In this paper, the application of these techniques in the control of induction machine (M.I) is presented. therefor, the fuzzy control of MI is handled. The fuzzy controlletr of 7 membership function (M.F) is used for speed control, offering the possibility of tuning its control parameters as a function of speed error. A M.F minimization of this controller is developped using fuzzy-neural technique
Artificial neural network control of the recycle compression system
(2014) Zammoum Boushaki, Razika; Chetate, Boukhmis; Zamoum, Y.
Artificial neuron network usage for asynchronous motor malfunction diagnostics in real-time operation mode
(2003) Chetate, Boukhmis; Khodja, Djalal Eddine
In the article it is told about the device of automatic diagnostics of electromechanical systems, which consists of two subsystems: a subsystem of acting data transformation and a subsystem of data processing. The first carries out data reception and their processing (distribution of data, estimation of parameters and their representation) while the second finds out failures (under the Artificial Neural Network help) which can occur in an electromechanical system and gives the recommendations for their elimination. However, the investigation of three Neural Networks have been proceeded to choose the most effective diagnostic failure Neural Network. In addition, to give the improve diagnostic, it is important to do the correct choice of parameters. According to made analysis stator current, rotation speed and acting signals are the most important parameters to be considered describing failures influence (their changes are essentially more in the defect occurrence case) and their physical values can be measured easily with the sensor
Bearing fault diagnosis based on current monitoring in asynchronous electrical machines using simplified higher-order statistics
(IOS Press, 2010) Djeddi, Mounir; Benidir, Messaoud; Djeddi, Mabrouk; Chetate, Boukhmis
Bearings fault diagnosis in asynchrounous machine based on current analysis using high resolution technique
(2007) Djeddi, Mounir; Granjon, Pierre; Leprettre, Benoit; Chetate, Boukhmis
In this Chapter, we propose to perform early fault diagnosis using spectral analysis based on high resolution MUSIC algorithm to detect bearings faults in electrical asynchronous machine. While most research works focus on mechanical vibration signals analysis. The originality of our work relies on the use of high-resolution method to stator current. We present the results obtained for real data of electrical signals to detect inner raceway and outer raceway bearings defects made articially as well as bearing defects obtained through element aging. The results shows that the proposed method yields better detection than classical spectum analysis
Choice of input data type of artificial neural network to detect faults in alternative current systems
(2006) Benslimane, T.; Chetate, Boukhmis
This paper present a study on different input data types of ANN used to detect faults such as overvoltage in AC systems (AC network , induction motor). The input data of ANN are AC voltage and current. In no fault condition, voltage and current are sinusoidal. The input data of the ANN may be the instantaneous values of voltage and current, their RMS values or their average values after been rectified. In this paper we presented different characteristics of each one of these data. A digital software C++ simulation program was developed and simulation results were presented
Compensation for the iron loss effect in EKF-based speed estimation of vector controlled induction motors
(IEEE, 2008) Kheldoun, Aissa; Chetate, Boukhmis
In vector controlled induction motor drives, the instantaneous rotor speed is measured using whether sensors or estimators. Since the basic Kalman filter is a state observer, its use in vector controlled schemes has received much attention. However, these schemes are based on the assumption that the existence of iron loss in an induction motor may be neglected. The paper shows the effect of iron loss on the extended Kalman filter performance that is designed on the basis if the ironless induction machine model. Simulation results are carried out to demonstrate this effect as well as the effectiveness of the suggested approach to minimise the speed estimation error without modifying the observer algorithm
Extended-Kalman-filter based sensorless speed vector control of induction motor taking iron loss into account
(Advances in Modelling and Analysis C, 2007) Chetate, Boukhmis; Kheldoum, A.
In vector controlled induction motor drives, the instantaneous rotor speed is measured using whether sensors or estimators. Since the basic Kaiman filter is a state observer, its use in vector controlled schemes has received much attention. However, these schemes are based on the assumption that the existence of iron loss in an induction motor may be neglected. The paper shows the effect of iron loss on the extended Kaiman filter performance that is designed on the basis if the ironless induction machine model. Original simulation results are carried out to demonstrate this effect as well as the effectiveness of the suggested approach to minimise the speed estimation error without modifying the observer algorithm
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
Implementation of SVPWM based on hysteresis control strategy applied on autonomous parallel active filter
(2005) Benslimane, T.; Aliouane, K.; Chetate, Boukhmis
This paper presents a study on the harmonic depollution of the electric power network as well as the compensation of reactive power by an autonomous three-phase active filter at parallel structure. The presentation of the system of filtering starts initially with the presentation of the modeling of the whole of the system network, parallel active filter and polluting load. In second place, the principle of identification of the harmonic currents by the method of the instantaneous real and imaginary powers is developed, followed by the presentation of the SPACE VECTOR PULSES WIDTH MODULATION BASED ON HYSTRERESIS applied to the inverter of the active filter. A strategy which makes it possible to control the inverter of the filter to generate the harmonic currents required with the optimization of the number of commutations of the semiconductors used. The following part is devoted to the presentation of regulation system of the terminal condenser voltage of the autonomous active filter and in the last are presented the digital simulation and experimental results
Influence of overvoltages in induction motors fed by PWM voltage inverters on power efficiency
(IEEE, 2007) Chetate, Boukhmis; Belassel, M.T.
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
Minimum action time of a robust fuzzy speed controller for induction machine drive
(Advances in Modelling and Analysis C, 2007) Chetate, Boukhmis; Bradai, Rafik
In this paper, we propose a procedure to design an optimal fuzzy controller for indirect field oriented controlled induction machine drives. This controller has best possible performances with a minimum action time possible in a practical implementation. First, we design a fuzzy PI controller having the maximum of fuzzy sets (7 input/output membership functions), which show better static and dynamic performances. This controller is specific to speed close loop of an indirect field oriented induction machine drive. Then, in order to minimize its composition the ANFIS (Adaptive Network-Based Fuzzy Inference System) structure is applied to perform a structural and parametric optimization of this controller. We propose also, a procedure to reproduce the input/output mapping of this controller with an approximation using artificial neural networks (ANN)
A new and best approach for early detection of rotor and stator faults in induction motors coupled to variable loads
(Higher Education Press, 2015) Allal, Abderrahim; Chetate, Boukhmis
A new diagnostic method of faulty transistor in a three-phase inverter
(2006) Benslimane, Tarak; Chetate, Boukhmis
This paper describes a method of detection and identification of transistor base drive open-circuit fault of 3-phase voltage source inverter (VSI), feeding an open loop controlled induction motor. The detection mechanism is based on a novel technique of wavelet transform. In this method, the stator currents will be used as an input to the system. No direct access to the induction motor is required. The simulation results are presented