Performance Of Direct Torque Control Research Articles

CONTRÔLE DIRECT DU COUPLE AVEC MODULATION VECTORIELLE SPATIALE UTILISANT DES RÉGULATEURS À LOGIQUE FLUUSE DE TYPE 2 À INTERVALLE D'UNE MACHINE À INDUCTION À DOUBLE ÉTOILE ALIMENTÉE PAR DEUX ONDULEURS À POINT NEUTRE À TROIS NIVEAUX SERRÉS

This paper introduces a direct torque control (DTC) method with space vector modulation (SVM) using interval type-2 fuzzy logic regulators for a dual-star induction machine fed by two three-level neutral point clamped inverters. The conventional DTC drive utilizes a pair of hysteresis comparators, which can lead to issues such as high torque ripple and variable switching frequency. As a result, we introduce several alternative methods, including DTC-SVM. We replace the hysteresis comparators with two Proportional-Integral (PI) regulators to enhance DTC performance, which generates the direct and quadrature voltage components in the d-q frame. The intricacy of the control system can make adjusting the PI regulator parameters difficult. To address this challenge, we propose using an interval type-2 fuzzy logic regulator for PI parameter adjustment in this paper. Our simulation results demonstrate the robustness and efficiency of the IT2FLC regulator.

Improvements the direct torque control performance for an induction machine using fuzzy logic controller

This article examines a solution to the major problems of induction machine control in order to achieve superior dynamic performance. Conventional direct torque control and indirect control with flux orientation have some drawbacks, such as current harmonics, torque ripples, flux ripples, and rise time. In this article, we propose a comparative analysis between previous approaches and the one using fuzzy logic. Results from the simulation show that the direct torque control method using fuzzy logic is more effective in providing a precise and fast response without overshooting, and it eliminates torque and flux fluctuations at low switching frequencies. The demonstrated improvements in dynamic performance contribute to increased operational efficiency and reliability in industrial applications.

FPGA implementation of a robust DTC-SVM based Sliding Mode Flux Observer for a double star induction motor: Hardware in the loop validation

This paper presents an implementation of a robust Direct Torque Control (DTC)-Space Vector Modulation (SVM) strategy for a Double Star Induction Machine (DSIM) using a Field Programmable Gate Array (FPGA). The proposed control technique combines SVM and DTC strategies, incorporating the Sliding Mode Flux Observer (SMFO) to improve robustness and overcome the drawbacks of stator resistance variations. First, SVM is used to improve DTC performance by reducing torque and flux ripples generated with classical DTC strategies. Then, the SMFO is employed to estimate the mechanical speed and stator flux module, ensuring robustness in the face of stator resistance variations. A comparative study between conventional DTC, DTC-SVM, and DTC-SVM-SMFO is presented. Simulation tests of the three DTC strategies were conducted using Matlab/Simulink tools, demonstrating the robustness and high performance of the DSIM under DTC-SVM-SMFO. To further validate these results, the technique was implemented using Xilinx System Generator (XSG) on a parallel processing software environment, the FPGA Virtex 5. Hardware in the loop results confirms the effectiveness of the DSIM under the improved DTC-SVM-SMFO control strategy.

Field programmable gate array hardware in the loop validation of fuzzy direct torque control for induction machine drive

Introduction. Currently, the direct torque control is very popular in industry and is of great interest to scientists in the variable speed drive of asynchronous machines. This technique provides decoupling between torque control and flux without the need to use pulse width modulation or coordinate transformation. Nevertheless, this command presents two major importunities: the switching frequency is highly variable on the one hand, and on the other hand, the amplitude of the torque and stator flux ripples remain poorly controlled throughout the considered operating speed range. The novelty of this article proposes improvements in performance of direct torque control of asynchronous machines by development of a fuzzy direct torque control algorithm. This latter makes it possible to provide solutions to the major problems of this control technique, namely: torque ripples, flux ripples, and failure to control switching frequency. Purpose. The emergence of this method has given rise to various works whose objective is to show its performance, or to provide solutions to its limitations. Indeed, this work consists in validation of a fuzzy direct torque control architecture implemented on the ML402 development kit (based on the Xilinx Virtex-4 type field programmable gate array circuit), through hardware description language (VHDL) and Xilinx generator system. The obtained results showed the robustness of the control and sensorless in front of load and parameters variation of induction motor control. The research directions of the model were determined for the subsequent implementation of results with simulation samples.

Artificial neural network-based DTC of an induction machine with experimental implementation on FPGA

Direct Torque Control (DTC) of Induction Machine (IM) has received increasing attention due to its high performance and low dependence on machine parameters. Recently, intelligent approaches have been proposed to improve the DTC performance, in particular the reduction in the torque and the flux ripples. In this paper, an approach for designing DTC for IMs that is based on Neural Network Control (NNC) is proposed. In this method, an artificial neural network, which can better manage the state of switches, is used instead of the switching table and two hysteresis controllers. The improvement is achieved by reducing the stator flux ripples and the torque ripples in the IM drive. The suggested architecture, which is developed using the VHDL, is designed using the modular architecture and the principles of the parallel architecture. The Direct Torque Neural Control (DTNC) simulation and experimental results are compared with those of the conventional DTC. Results of the comparison demonstrate how the DTNC reduces torque ripples and stator flux ripples. Results from simulation and experiment are used to verify how effectively the suggested control works. The ZC702 SOC, which is Xilinx Board based on Zynq FPGA, has been selected for experimental implementation.

Primena fazi logičkog kontrolera tipa 2 i kontrolera frakcionog reda za regulisanje brzine direktnog upravljanja momentom sile u indukcionom motoru

Introduction/purpose: Among excellent strategies available to control the torque of asynchronous motors, we distinguish direct torque control. This technique of control allows direct control of magnetic flux and electromagnetic torque without the need to decouple them. Also, direct torque control like each control strategy has some drawbacks, the major drawbacks of this technique being operation at a variable switching frequency and flux and electromagnetic ripples due to the use of hysteresis regulators. It worsens acoustic noise, especially at low speeds, as well as the control performances. Methods: To improve the performance of direct torque control especially at low speeds, the authors propose using fractional order PID in combination with type-2 fuzzy logic controllers to regulate the speed of an induction motor controlled by direct torque control. Results: The results obtained by the proposed regulators show the improvements made to the system. Conclusion: The proposed contribution can exert better control efforts.

Direct Torque Control With Variable Flux for an SRM Based on Hybrid Optimization Algorithm

This article presents an optimal direct torque control (DTC) strategy with variable flux for a switched reluctance motor using the improved linear active disturbance rejection control (LADRC) plus the hybrid optimization algorithm (HOA). First, the constant flux amplitude is substituted by the variable flux DTC (VF-DTC) to reduce the torque ripple. Then, the LADRC with the improved extended state observer applied in speed controller is utilized instead of the conventional PI control to improve the speed of the observer, antidisturbance ability, and robustness. Moreover, the HOA is employed to search for the optimal control parameters and acquire satisfactory dynamic performances. Finally, the optimal VF-DTC system is implemented on a 12/8 SRM. Simulation and experimental results are carried out to compare the performances of the conventional DTC, the VF-DTC with LADRC, the VF-DTC with PI using HOA, and the proposed optimal VF-DTC using HOA. The results show that the proposed control method has a faster speed response, superior antidisturbance ability, and lower torque ripples.

Improvement of Steady State Performance for Rotating Vector-Based Direct Torque Control

Matrix converter (MC) rotating vector (RV) has the natural advantage for common-mode voltage (CMV) minimization. However, the application of RV in direct torque control (DTC) strategy for motor drive system is limited, mainly due to the extensive torque ripple and current distortion. To improve the steady state torque and current performance of the traditional RV-based DTC, a novel RV- based DTC method is proposed in this paper. According to the analysis of the angle offset between stator flux and the candidate voltage vector, the vector plane is divided into 12 sectors, and virtual vector synthesized by two adjacent rotating vectors is employed to fill in the blank sectors. Based on this, a 12 sector- switching table combined with a novel mapping table of rotating vectors are established to fulfill the proposed RV-DTC method. Experiments are carried out to verify the proposed method. The results show that compared with the traditional RV-DTC, steady state torque and current performances are evidently improved with the proposed RV-DTC at approximate switching frequency, while zero CMV is reserved.

Induction Motor DTC Performance Improvement by Reducing Flux and Torque Ripples in Low Speed

Since induction motors were invented, human civilization has changed forever. Due to their beneficial characteristics, induction motors are widely used and have become the most prevalent electrical counterparts. Many control strategies for induction motors have been developed, varying from scalar to vector control. In the class of vector control, the Direct Torque Control (DTC) was proposed as an alternative that ensures separated flux and torque control while remaining completely in a stationary reference frame. It offers direct inverter switching, reasonable simplicity than other vector control techniques, and less sensitivity to parameter variation. However, the use of hysteresis controllers in conventional DTC involves non-desired ripples in the system's flux and torque, which leads to bad system performances, primarily in low-speed operations. This paper aims to minimize the chattering and ensure the augmented system's performance in terms of robustness and stability. The proposed method is an improved version of DTC, which combines the addition of the Space Vector Machine (SVM) algorithm to the DTC and the increased number of DTC sectors that generate reference control voltages. Satisfactory results have been obtained by numerical simulation in MATLAB/Simulink. Eventually, the proposed method is proven to be a fast dynamic decoupled control that robustly responds to external disturbance and system uncertainties, especially in the low-speed range.

Model Predictive Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) with Online Parameter Estimation Based on Extended Kalman Filter

Aiming at the torque and flux ripples in the direct torque control and the time-varying parameters for permanent magnet synchronous motor (PMSM), a model predictive direct torque control with online parameter estimation based on the extended Kalman filter for PMSM is designed. By predicting the errors of torque and flux based on the model and the current states of the system, the optimal voltage vector is selected to minimize the error of torque and flux. The stator resistance and inductance are estimated online via EKF to reduce the effect of model error and the current estimation can reduce the error caused by measurement noise. The stability of the EKF is proved in theory. The simulation experiment results show the method can estimate the motor parameters, reduce the torque, and flux ripples and improve the performance of direct torque control for permanent magnet synchronous motor (PMSM).

An improved look-up table-based direct torque control for permanent magnet synchronous generator using Vienna rectifier

This paper presents an improved look-up table-based direct torque control of the permanent magnet synchronous generator using Vienna rectifier for a wind energy conversion system. A stator voltage model for the system was developed to allow an in-depth analysis of the effect of the switching vectors for the Vienna rectifier on the performance of direct torque control. The developed generator model is dedicated to reducing the complexity of look-up table development. Subsequently, an improved look-up table was designed to enhance the overall performance of the permanent magnet synchronous generator in both torque and stator flux ripples, along with the investigation of the computation delay compensation for the digital implementation. The performance was first investigated through Matlab / Simulink before being further validated using a small-scale prototype and a wind turbine emulator. Both simulation and experimental results obtained were compared with the existing direct torque control approach to verify the effectiveness of the proposed system for wind energy extraction. The results show that the enhanced look-up table generates lower ripples in torque and stator flux while improving their reference tracking, especially during unbalanced DC load scenarios. This achievement can be clearly seen by the lower discrepancy percentage between the reference and actual value in the generated torque and stator flux by 6.35% and 0.47%, respectively.

Sensorless Direct Torque Control of PMSM Based on Fuzzy Sliding Mode Control with Full Order Sliding Mode Observer

This paper presents an implementation of Fuzzy Sliding Mode Control for Sensorless Direct Torque Control (DTC) of a Permanent Magnets Synchronous Machine as a combination between the known performances of direct torque control on the one hand and the robustness of sliding mode control on the other hand. The fuzzy controller is introduced to reduce the effect of chattering phenomenon which is the major disadvantage of sliding mode control technique. The proposed controller is used to replace the conventional PI angular speed controller that generates the electromagnetic reference torque for DTC, in order to improve the dynamic and the permanent behaviors of the angular speed control response as well the electromagnetic torque. The proposed control technique is implemented without using speed or position sensors, where a Full Order Sliding Mode Observer is used. It is shown that the proposed control technique has given improved simulation results with different speed ranges and different load values.

Intelligent control of induction motor for photovoltaic water pumping system

This work aims to improve the performance of direct torque control (DTC) technique for induction motor based photovoltaic (PV) water pumping system (PVWPS). The innovative aspect of this work consists in introducing the adaptive fuzzy logic control and the fuzzy logic control techniques as alternative approaches to conventional DTC to control the PVWPS. To ensure a good operation of the PV array, a variable step size incremental conductance (VSS INC) is implemented. Simulation studies of the proposed topology based on intelligent approaches will be investigated using Matlab/Simulink under various operating conditions to validate the suitability of the proposed PVWPS. From the obtained results, the proposed control strategies appear to be very convenient for water pumping applications.Article HighlightsAn intelligent control based on the advanced techniques is proposed for PV water pumping system.An adaptive fuzzy logic PID approach and optimal fuzzy rules are proposed for better operation of PV system.The suggested PV water pumping system achieves better performance, in particular minimization of torque and flux ripples, reduction of torque overshoot and high dynamic response.

The Operation of UAV Propulsion Motors in the Presence of High External Magnetic Fields

The operation and maintenance of converter stations (also known as valve halls) in high voltage DC (HVDC) grids is a key element in long-term, reliable and stable operation, especially in inherently adverse offshore environments. However, the nature of the electromagnetic field environment inside HVDC valve halls presents a challenge for the operation of traditional off-shelf inspection robots. In this paper, the impact of the external magnetic field on the operation of an inspection UAV’s propulsion motors is assessed. An experimental method is proposed to simulate the maximum magnetic field interference to off-shelf UAV motors, which can be used to identify their suitability for use in HVDC valve halls inspection robots. The paper’s experimental results compare the performance of direct torque control and field-oriented control algorithms for propulsion motors under the influence of external magnetic flux. Under the influence of a 177 mT external magnetic field, it was found that using direct torque control, the motor rotational velocity steady-state error was up to 55%. With field-oriented control, the steady-state error was 0%, however the peak-to-peak current draw increased by up to 567%.

Hybrid bacteria foraging-particle swarm optimization algorithm in DTC performance improving for induction motor drive

<p dir="ltr"><span>This paper presents a hybrid algorithm that combines the particle swarm optimization method with the bacteria foraging technique, named: BF-PSO. The aim is to achieve more efficient and precise parameters determination of the regulators that leads to performance improvement in the speed-loop control of an induction motor (IM) implemented in a direct torque control (DTC). The approach consists of tuning the proportional-integral (PI) parameters that meet high dynamics and tracking behavior using the hybrid BF-PSO algorithm. </span>Investigations have been completed with Matlab/Simulink and several performance tests are conducted. The comparison results are exposed with the most used indices in the controllers' tuning with optimization techniques. It will be shown that the presented technique presents better quality results compared to the conventional method of calculated PI.</p><div><span><br /></span></div>

Improved Performance of Direct Torque Control with PMSM compared to DTC with Induction Motor

For induction motor torque control, direct torque control is becoming the industry standard. This paper proposes a switching loss minimization technique for improved Direct Torque Control (DTC) of permanent magnet synchronous motors in order to increase the drive system's steady-state and dynamic results. Direct torque control (DTC) of a voltage source inverter-supplied PMSM is a simple scheme that requires little computation time, can be implemented without speed sensors, and is unaffected by parameter variations. In theory, the motor terminal voltages and currents are used to calculate the flux and torque of the motor. A voltage vector is chosen to restrict the flux and torque errors within their flux and torque hysteresis bands based on the instantaneous torque and stator flux magnitude errors, as well as estimates of the flux position. The electromagnetic torque, rotor speed, and stator current of DTC with PMSM and DTC with IM were successfully calculated using Total Harmonic Distortion (THD) in this article. As compared to DTC with IM, DTC with PMSM reduced THD by 12 percent in torque, speed, and stator current [21]. Switching Losses Minimization Technique by THD Minimization is used in this article. Since transistors are only switched when necessary to maintain torque and flux within their hysteresis limits, switching losses are minimised, resulting in increased efficiency and lower losses. Matlab SIMULINK has experimentally confirmed direct torque regulation with PMSM and IM.

Sensorless direct torque control based on seven-level torque hysteresis controller for five-phase IPMSM using a sliding-mode observer

This paper proposes sensorless control of the seven-level torque hysteresis controller (7LTHC) in the direct torque control (DTC) method for five-phase interior permanent magnet synchronous motor (IPMSM). Both torque response and torque ripples of the machine are directly related to the amplitude and location of voltage vectors in the hysteresis DTC method. Additionally, different level torque hysteresis controllers are used to configure a variety of voltage vectors. In this paper, 7LTHC is compared with three-level hysteresis torque controllers (3LTHCs) by using different amplitude voltage vectors to validate the DTC based on the proposed 7LTHC method in Matlab/Simulink environment. Dynamic torque response in the transient operation and low torque ripple and low stator current harmonics in the steady-state operation can be achieved by using the proposed 7LTHC. Furthermore, the speed of IPMSM which is controlled by the DTC based on the proposed 7LTHC is estimated using a sliding-mode observer (SMO) based on sigmoid function and the speed performance is enhanced by combining angle tracking observer (ATO) with the SMO. The simulation results confirm the performance of DTC based on the proposed 7LTHC using the structure of hysteresis DTC and the mathematical model of five-phase IPMSM which uses an SMO for sensorless speed control.

PI Regulator-Based Duty Cycle Control to Reduce Torque and Flux Ripples in DTC of Six-Phase Induction Motor

In this paper, a proper duty cycle control method is proposed to reduce torque and flux ripples and harmonic loss in direct torque control (DTC) of six-phase induction machine (6PIM). Three different methods are proposed to improve the performance of switching table DTC for 6PIM. First, by the suitable selection of two vectors in each sampling period, the harmonic amplitude is significantly decreased, but the torque and flux ripples are still large. Then, the abovementioned method is combined with duty cycle control technique and the torque and flux ripples and current harmonics are significantly reduced. In addition, the switching frequency is also reduced by selecting the suitable voltage vector in each sampling period. Finally, a simple control method is suggested to calculate the duty ratio of voltage vectors independently of machine parameters. Although neglecting the one-step delay makes performance of the final technique similar to the previous one, considering this delay in real conditions shows the following advantages for the final method: less torque and flux ripples, less current harmonics, simplicity, and constant switching frequency. Despite these improvements, all duty cycle-based DTC approaches (duty-DTC and PI-duty-DTC) increase the inverter switching losses. The simulation and experimental results presented in this paper verify the performance advantages of the proposed methods.

Artificial Neural Networks Applied to a Wind Energy System

In this context, we are taking a close interest in the optimization of wind energy production. It consists in designing simple to implement control strategies of a wind energy conversion system, connected to the network based on the Double Fed Induction Generator (DFIG) driven by the Converter Machine Side (CSM) in order to improve the performance of Direct Torque Control (DTC) and Direct Power Control (DPC). For this purpose, the artificial neural networks (ANNs) is used. Hysteresis comparators and voltage vector switching tables have been replaced by a comparator based on artificial neural networks. The same structure is adopted to build the two neural controllers, for the DTC – ANN and for the DPC – ANN. The simulation results show that the combination of classical and artificial neural network methods permit a double advantage: remarkable performances compared to the DTC-C and DPC-C and a significant reduction of the fluctuations of the output quantities of the DFIG and especially the improvement of the harmonics rate currents generated by the machine.

Neural Direct Torque Control for Induction Motor under Voltage Source Inverter Open Switch Fault

Background: The study of induction motor behavior during abnormal conditions due to the presence of faults and the possibility to diagnose these abnormal conditions has been a challenging topic for many electrical machine researchers. Objective: Direct Torque Control (DTC) is applied to the control of an induction motor in healthy and an open circuit fault in the PWM three phase voltage fed inverter. Neural DTC is developed and used to improve the dynamic behavior of the drive system under faulty switch occurrence. Methods: The validity of the proposed control scheme is tested under normal conditions and switching fail in the Voltage Source Inverter (VSI) caused by an open circuit. Through a simulation testing of an induction motor drive system at different speed references, a comparison between basic DTC and Neural DTC is performed. Results: Simulated results on 1.5-kW induction motor drive show the performance of the proposed control in normal and faulty cases. The stator current, flux, torque, and speed at different references are determined and compared in the above techniques using MATLAB-SIMULINK. Conclusion: A Neural Network (NN) DTC control system under an open switch fault is proposed without the need for classical switching table. The use of hybrid intelligent techniques aims to improve the DTC performances in case of multiple faults occurrence.