Farhat Fnaiech

Fuzzy Logic and Sliding-Mode Controls Applied to Six-Phase Induction Machine With Open Phases

The faulted mode of a six-phase induction machine (6PIM) denotes that the motor is working with one or more missing phases. This situation leads to torque oscillations and poor tracking behavior. Therefore, the design of a suitable robust control is a challenging task. In this way, this paper presents the application of fuzzy logic and sliding mode controls in order to obtain a high-accuracy positioning of a 6PIM rotor in both healthy and faulted modes. The two control strategies are completely different from a theoretical point of view, but the final objectives are to remove the drawbacks of the specific fault on interest. The experimental results are obtained on a dedicated setup based on a 6PIM coupled with a variable mechanical load and for which up to three phases can be removed.

A fast feedforward training algorithm using a modified form of the standard backpropagation algorithm

In this letter, a new approach for the learning process of multilayer feedforward neural network is introduced. This approach minimizes a modified form of the criterion used in the standard backpropagation algorithm. This criterion is based on the sum of the linear and the nonlinear quadratic errors of the output neuron. The quadratic linear error signal is appropriately weighted. The choice of the weighted design parameter is evaluated via rank convergence series analysis and asymptotic constant error values. The new proposed modified standard backpropagation algorithm (MBP) is first derived on a single neuron-based net and then extended to a general feedforward neural network. Simulation results of the 4-b parity checker and the circle in the square problem confirm that the performance of the MBP algorithm exceed the standard backpropagation (SBP) in the reduction of the total number of iterations and in the learning time.

Linear and Nonlinear Control Techniques for a Three-Phase Three-Level NPC Boost Rectifier

This paper deals with three control techniques for a three-phase three-level neutral-point-clamped (NPC) boost rectifier to study their relative performance. Linear, nonlinear, and nonlinear model reference adaptive control (MRAC) methods are developed to control power factor (PF) and regulate output and neutral point voltages. These controllers are designed in Simulink and implemented in real time using the DS1104 DSP of dSPACE for validation on a 1.2-kW prototype of an NPC boost rectifier operating at 1.92 kHz. The performance of boost converter with three control methods has been investigated respectively in steady state in terms of line-current harmonic distortion, efficiency, and PF and during transients such as load steps, utility disturbances, reactive power control, and dc-bus voltage tracking behavior. The linear PI controllers are characterized by reduced complexity but poor performance, whereas the nonlinear control technique has improved the converter performance significantly, while nonlinear MRAC exhibits much better performance in a wide operating range

Nonlinear control strategy applied to a shunt active power filter

This paper presents a new nonlinear decoupling control method of a three-phase three-wire voltage source shunt active filter. The currents injected by the active filter are controlled in the synchronous orthogonal dq frame using a decoupled feedback linearization control method. The reference currents are extracted from the sensed nonlinear load currents by applying the synchronous reference frame method. The voltage level of the DC side is regulated using an output feedback linearization control. Integral compensators are added in both current and voltage loops in order to eliminate the steady state errors due to system parameters uncertainty. Simulation results confirm the performance considered theoretically for the shunt active filter.

A DSP-based implementation of a new nonlinear control for a three-phase neutral point clamped boost rectifier prototype

This work presents the design and implementation of a nonlinear control strategy for a three-phase three-level neutral-point-clamped boost rectifier. The adopted control consists of nonlinear feedback linearization technique. The nonlinear state-space model of the rectifier was obtained in the dq0 reference frame. The input/output feedback linearization is then applied and the linearizing control law is derived. Therefore, the resulting model is linearized and decoupled in three independent subsystems. Afterwards, the stabilizing controllers are designed based on linear techniques to control line currents, output, and neutral point voltages. The control law is designed using Simulink/Matlab and applied to the converter via a 1.8-kHz pulsewidth modulator (PWM). Both control law and PWM signals are executed in real time using the DS1104 DSP of dSPACE. A 1.2 kW laboratory prototype is built for validation purposes. The proposed control law robustness is validated for diverse severe load and system parameter variations. It shows robust performance in terms of high power factor, low total harmonic distortion and output voltage ripples, small overshoot, and short settling time.

A series hybrid power filter to compensate harmonic currents and voltages

In this paper a series hybrid power filter (SHPF) to compensate harmonic currents and voltages at PCC is proposed. The SHPF consists of a small-rated series active power filter (SRSAPF) and a series tuned passive filter (STPF). This combination is suitable for compensating voltage type harmonics-producing load. The SHPF uses the synchronous rotating frame method, which detects both source current and load voltage harmonics. Simulation results using Power System Blockset Toolbox PSB of Matlab show the performance of the series hybrid power filter, and its capability to compensate for voltage type harmonics-producing load.

Color image segmentation using automatic thresholding and the fuzzy C-means techniques

In this paper, a color image segmentation approach based on automatic histogram thresholding and the fuzzy C-means (FCM) techniques is presented. The originality of this work remains in using thresholding and clustering techniques together for color image segmentation. The histogram considers the occurrence of the gray levels among pixels. In a first stage, the thresholding histogram is used for finding all major homogenous areas. In order to reduce the computational burden required by the fuzzy C-means, the coarse-fine concept methodology is used. The thresholding technique is used for the coarsely segmentation. After the coarse step, and in order to refine further the segmentation of the assigned pixels which remain unclassified, the fuzzy C-means technique is then applied. The experimental results show that the proposed approach can find homogeneous areas effectively, and can solve the problem of discriminating shading in color images to some extent.

A new control technique based on the instantaneous active current applied to shunt hybrid power filters

This paper presents a new indirect current control technique based on the instantaneous active current applied to shunt hybrid power filters (SHPF) to compensate harmonics and the reactive power of a nonlinear load. This method uses a residual signal constructed from the comparison between the supply currents and their desired values. To evaluate its performance, this method is compared to the direct current control technique based on the synchronous frame method. The switch patterns are greatly reduced. The ripples in the supply currents shapes are eliminated and the proportional gain K/sub p/ is automatically set. While its determination is a hard task using direct methods. A three-phase current controlled voltage source inverter feeds the primary windings of the transformer. The SHPF damps the resonant frequency created by source inductance and power factor correction capacitors to a noncritical value. Simulation results using Power System Blockset Toolbox PSB of Matlab show the performance of the proposed control algorithm with a reduced switch AF circuit and its capability to compensate for harmonics and reactive power.

A Suitable Initialization Procedure for Speeding a Neural Network Job-Shop Scheduling

Artificial neural network models have been successfully applied to solve a job-shop scheduling problem (JSSP) known as a Nonpolynomial (NP-complete) constraint satisfaction problem. Our main contribution is an improvement of the algorithm proposed in the literature. It consists in using a procedure optimizing the initial value of the starting time. The aim is to speed a Hopfield Neural Network (HNN) and therefore reduce the number of searching cycles. This new heuristic provides several advantages; mainly to improve the searching speed of an optimal or near optimal solution of a deterministic JSSP using HNN and reduce the makespan. Simulation results of the proposed method have been performed on various benchmarks and compared with current algorithms such as genetic algorithm, constraint satisfaction adaptive neural networks, simulated annealing, threshold accepting, flood method, and priority rules such as shortest processing time (SPT) to mention a few. As the simulation results show, and Brandts algorithm, combined with the proposed heuristic method, is efficient with respect to the resolution speed, quality of the solution, and the reduction of the computation time.

Input filter design for SVM Dual-Bridge Matrix Converters

This paper gives a simple procedure to size the input filter parameters for DBMC. The proposed methodology performs a reasonable THD of the line current as well as a compromise between the input power factor and the THD of the input filter capacitor voltage. On the other side, the input filter performances are evaluated in detail when the converter is controlled by a SVM scheme. Finally, future trends are proposed to overcome the observed drawbacks by using advanced control strategies.