ANT-colony optimization-direct torque control for a doubly fed induction motor: An experimental validation

Direct Torque Control (DTC) presents an optimal solution to control the behaviors of the alternative motors, compared to other controls, because of several advantages offered by this technique, the speed overshoots, fluxes, and torque ripples remain the major factors which minimize the DTC robustness. The regulation speed in DTC is carried out by the classic Proportional Integrator Derivative (PID), which is known for its higher robustness in linear systems, except that in the case of non-linear systems, the PID controller gives poor reactions to variations in the system's parameters. The best solutions adopted in this situation are often based on optimization algorithms that generate the controller's gains in each period where there is an internal or external perturbation, adapting the behaviors of the PID against the system's nonlinearity. For that reason, this work is focused on the theoretical studies and experimental validation on dSPACE Board DS1104 of the new proposed approach based on PID speed regulation, optimized by the Ant Colony Optimization algorithm (ACO) for DTC, applied to both sides of the Doubly Fed Induction Motor (DFIM), to overcome the previous drawbacks cited at the beginning. The new combined ACO-DTC strategy has been studied for optimizing the gains of the PID controller by using a cost function such as Integral Square Error (ISE). The proposed approach is implemented on Matlab/Simulink to validate the objectives adopted by this strategy. The simulation and experimental results extracted from Matlab and ControlDesk have proved the efficiency of the proposed ACO-DTC with the system's nonlinearity, which attribute different enhancements in the global system performance.This publication was made possible by Qatar University Collaborative Research grant # [ QUCG-CENG-21/22-1 ] from the Qatar University. The statements made herein are solely the responsibility of the authors. The APC is funded by the Qatar NAtional Library, QatarScopu

Contribution to the Improvement of the Performances of Doubly Fed Induction Machine Functioning in Motor Mode By the DTC Control

In this article, we are interested in the improvement of the performances of Doubly Fed Induction Machine (DFIM) operating in motor mode by the use of the direct torque control (DTC). Firstly, we focused on the modeling of the DFIM and the study of the principle of functioning of the DTC control. Then, we implement this control on the Matlab/Simulink environment. Secondly, we present the simulation results of the proposed control. The analysis of these results shows clearly that the system based on the DFIM studied follows perfectly the set points, what allowed us to justify the efficiency of the elaborate control

Field Oriented Control of Doubly Fed Induction Motor using Speed Sliding Mode Controller

This article presents a modeling and control of the Doubly Fed Induction Motor (DFIM), associated with two inverters controlled through the Pulse Width Modulation technique (PWM), the control of the DFIM is carried out by the approach of Rotor Flux Oriented Control (RFOC) according to the direct axis. In this approach, regulation is done by classic PI regulators, the latter having undesirable overruns and static errors in non-linear systems, for that the introduction of the control by sliding mode in place of the classic PI speed regulator, that is in the form of a control law based on this type of controller since it is invariant to the non-linearity of the system and precise, stable, simple and has a good response time, in order to validate the objectives of improving the DFIM behavior in front of the reference parameters, such as the speed and the torque imposed on the machine. The results of the proposed approach are validated by its implementation on the Matlab/Simulink environment

Enhancing the Performance of a Renewable Energy System Using a Novel Predictive Control Method

The current study concerns improving the performance of a renewable energy system using systematically designed control algorithms. The performance of the system under study is evaluated under two operating scenarios: the first in which the system consists of only a wind-driven synchronous generator connected to the utility grid; in the second scenario, the generator is combined with a photo-voltaic solar system and a battery for supplying a load. Each system component is modeled and thoroughly described. To maximize the benefits of solar and wind energies, two separate maximum power point tracking procedures are adopted. Furthermore, to enhance the generator’s dynamics, a novel predictive control scheme is designed and validated by comparing its performance with traditional predictive control. The novel predictive controller utilized a simple and unique cost function to avoid the shortages of traditional predictive controllers. For standalone operation, an effective procedure is adopted to ensure the power balance between the generation, storage, and isolated load units. To evaluate the effectiveness of the designed controllers under different operating regimes, Matlab/Simulink is utilized for this task. The obtained results confirm the superiority of the novel predictive scheme used with the synchronous generator over the classic control approach for the two operating scenarios. This has been shown in the form of reduced ripples and reduced current harmonics. The obtained results are also confirming the validity of the adopted maximum power tracking strategies with solar panels and wind turbines as well. Furthermore, balanced power delivery is achieved thanks to the adopted management strategy for standalone operation, which enhances the overall system performance

Optimization and control of water pumping PV systems using fuzzy logic controller

International audienceThe aim of this work is to search for better control and optimization of a photovoltaic (PV) water pumping system (PWPS) using the induction motor. A proposed method based on Fuzzy Logic Control (FLC) is introduced and investigated to improve the conventional Direct Torque Control (DTC). Variable step size Perturb and observe (P&O) is used to extract the maximum possible power from the PV panel. The validation of the control strategy is ensured by reducing the high torque, stator flux ripples and current harmonics in induction machine and increasing pumped water flow. Simulation results of the DTC based on FLC are compared with those of the conventional DTC using MATLAB/SIMULINK. The comparison results show the effectiveness of the FLC controller in terms of torque and flux ripples reduction, and daily pumped water

Improved DTC strategy of doubly fed induction motor using fuzzy logic controller

International audienceThis paper presents an improved Direct Torque Control (DTC) strategy for a Doubly Fed Induction Machine (DFIM) powered by two voltage source inverters (VSI) at two levels. This strategy is based on the fuzzy logic controller. The main objective is to improve the performance of the system by reducing electromagnetic torque ripples and improving the currents shape by optimization of the total harmonic distortion (THD). The hysteresis regulators and voltage vectors selection table of the conventional DTC are replaced by fuzzy logic blocks to realize fuzzy DTC control. The two control strategies are simulated in the MATLAB/SIMULINK environment followed by a comparative analysis to validate the effectiveness of the proposed strategy. Many improvements in term of rise time, torque ripples, flux ripples and current harmonics have been done, namely stator and rotor flux ripple and torque ripple have been reduced more than 50%, 69.2% and 47.7% respectively. The stator and rotor currents THD have been reduced around 84.5% and 84.3% respectively

Modern improvement techniques of direct torque control for induction motor drives - a review

International audienceThe aim of this work is to search for better control and optimization of a photovoltaic (PV) water pumping system (PWPS) using the induction motor. A proposed method based on Fuzzy Logic Control (FLC) is introduced and investigated to improve the conventional Direct Torque Control (DTC). Variable step size Perturb and observe (P&O) is used to extract the maximum possible power from the PV panel. The validation of the control strategy is ensured by reducing the high torque, stator flux ripples and current harmonics in induction machine and increasing pumped water flow. Simulation results of the DTC based on FLC are compared with those of the conventional DTC using MATLAB/SIMULINK. The comparison results show the effectiveness of the FLC controller in terms of torque and flux ripples reduction, and daily pumped water.Conventional direct torque control (DTC) is one of the excellent control strategies available to control the torque of the induction machine (IM). However, the low switching frequency of the DTC causes high ripples in the flux and torque that leads to an acoustic noise which degrades the control performances, especially at low speeds. Many direct torque control techniques were appeared to remedy these problems by focusing specifically on the torque and flux. In this paper, a state of the art review of various modern techniques for improving the performance of DTC control is presented. The objective is to make a critical analysis of these methods in terms of ripples reduction, tracking speed, switching loss, algorithm complexity and parameter sensitivity. Further, it is envisaged that the information presented in this review paper will be a valuable gathering of information for academic and industrial researchers

Optimization of a Solar Water Pumping System in Varying Weather Conditions by a New Hybrid Method Based on Fuzzy Logic and Incremental Conductance

The present work consists of developing a new hybrid FL-INC optimization algorithm for the solar water pumping system (SWPS) through a SEPIC converter whose objective is to improve these performances. This technique is based on the combination of the fuzzy logic of artificial intelligence and the incremental conductance (INC) technique. Indeed, the introduction of fuzzy logic to the INC algorithm allows the extraction of a maximum amount of power and an improvement in the efficiency of the SWPS. The performance of the system through the SEPIC converter is compared with those of the direct coupling to show the interest of the indirect coupling, which requires an adaptation stage driven by an optimal control algorithm. In addition, a comparative analysis between the proposed hybrid algorithm and the conventional optimization techniques, namely, P&O and INC Modified (M-INC), was carried out to confirm improvements related to the SWPS in terms of efficiency, tracking speed, power quality, tracking of the maximum power point under different weather changes, and pumped water flow

Bearing Fault Diagnosis for an Induction Motor Controlled by an Artificial Neural Network—Direct Torque Control Using the Hilbert Transform

Motor Current Signature Analysis (MCSA) is a popular method for the detection of faults in electric motor drives, particularly in Induction Machines (IMs). For Bearing Defects (BDs), which are very much related to the rotational frequency, it is important to maintain the speed at a target reference value in order to distinguish and locate the different BDs. This can be achieved by using a powerful control such as the Direct Torque Control (DTC), but this control causes the variation of the supply frequency and the current signal to become non-stationary, so the integration of advanced signal processing methods becomes necessary by using a suitable filter to handle the frequency content depending on the BDs, such as the Hilbert filter. This paper aims to adopt the Hilbert Transform (HT) for extracting the signature of the faults from the stator current envelope to detect the different BDs in the IMs when they are controlled by an intelligent DTC control driven by Artificial Neural Networks (ANN-DTC). This ANN-DTC control is a shaping factor rather than a disturbing one, which contributes with the Hilbert filter to the diagnosis of BDs. This technique is tested for the four locations of BDs: the inner ring, the outer ring, the ball, and the bearing cage in different operating situations without control and with conventional DTC and ANN-DTC controls. Thus, detecting the location of the defect exactly at an early stage contributes to achieving maintenance in a fairly short time. The performance of the chosen approach lies in minimizing the electromagnetic torque ripples as a result of the control and increase of the amplitudes of the spectra related to BDs compared to other harmonics. This performance is verified in the MATLAB/SIMULINK environment