Direct Torque Control Method Research Articles

Direct Instantaneous Torque and Axial Force Control Method for Linear-Rotary Switched Reluctance Motor With Two Radial Windings

Direct Instantaneous Torque and Axial Force Control Method for Linear-Rotary Switched Reluctance Motor With Two Radial Windings

Experimental Implementation of a TD3 Agent Based Speed Controller for Direct Torque Control of PMSM Drives

This manuscript presents a novel control approach for Permanent Magnet Synchronous Motors (PMSMs) by integrating the widely used Direct Torque Control (DTC) method with Deep Reinforcement Learning (DRL), specifically the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. The TD3 algorithm is well-suited to address the challenges posed by high-dimensional state and action spaces in PMSM drives. The conventional Proportional–Integral (PI) controller in the outer loop of DTC is replaced with the DRL based TD3 agent to overcome the limitations of traditional PI controllers, such as model dependency and complex parameter tuning. The DRL technique allows the agent to learn optimal control policies from experience, making it suitable for complex and nonlinear control problems. Extensive simulation studies demonstrate the effectiveness of the TD3-based control in achieving accurate speed tracking under varying operating conditions. Real-time experimental validation using a TMS320F28379D digital signal processor confirms the feasibility of the proposed DRL based approach. The research offers new insights into improving the performance of PMSM drives and paves the way for future advancements in electric drive control.

Experimental investigation of predictive control for PMSM-based wind turbine generation system

The theoretical analysis of permanent magnet synchronous machine (PMSM)-based wind turbine generation system was presented by many researchers; nevertheless, although the practical setup is still quite difficult, it is more valid. Moreover, the main challenge facing wind power systems is figuring out how to extract the most energy from varying wind speeds. Since wind turbine maintenance is hard and expensive, using wind speed sensors is a challenging operation. Therefore, this research suggests an effective and practical control system based on the Model Predictive Control Scheme (MPCS) for both the grid-side converter (GSC) and the machine-side converter (MSC) to optimize power extraction from wind energy. Detailed exploration of the MPCS for the PMSM and predictive power control (PPC) for the GSC involves stages such as flux estimation, torque prediction, and cost function minimization. The results obtained validate the higher performance of MPCS in comparison to the direct torque control (DTC) method. Furthermore, excellent tracking with high accuracy is achieved in relation to simulation and experimental data. Additionally, an evaluation indices based on root mean square error (RMSE) and gross system efficiency are used for wind turbine performance. These indices are used to show that, the feasibility of the MPCS approach compared with DTC under the same WT conditions. This approach offers a promising avenue for cost-effective wind energy conversion. The control systems were designed and implemented utilizing a DSPACE 1104 card. Experimental results confirm the effectiveness of the proposed mechanism in achieving maximum power point tracking (MPPT).

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.

Optimizing DFIG‐DC system performance via model predictive control: Torque ripple, DC voltage drop, and THD reduction

AbstractIn this study, two novel control methods are theoretically introduced as direct slip angle control (DSAC) and model predictive direct slip angle control (MPDSAC) for rotor side converter (RSC) of the standalone Doubly‐Fed Induction Generator (DFIG)‐DC system (S‐DFIG‐DC). The numerical analysis of the proposed methods demonstrated that the proposed DSAC method could reduce torque ripple and current harmonics, decrease the output DC voltage drop in fast changes of load condition, and have faster dynamic response. Also, the MPDSAC method could further diminish torque and flux ripple, current harmonics, and output DC voltage drop in sharp changes of load condition compared with the presented DSAC and direct torque control (DTC) methods. The sensitivity analysis of the proposed control methods is investigated at different operating conditions. The performance and usefulness of the DSAC and MPDSAC schemes are verified by various experiments and compared with the conventional DTC method.

An Improved Control Method for Direct Torque Control Based on Sliding Mode Control

An Improved Control Method for Direct Torque Control Based on Sliding Mode Control

Higher performance enhancement of direct torque control by using artificial neural networks for doubly fed induction motor

Recently Direct Torque Control is widely appreciated compared to other conventional control methods due to its numerous advantages, notably its speed and precision. However, despite its qualities, it often encounters torque ripples that limit its operational effectiveness. These variations can be attributed to the use of hysteresis comparators, leading to variable frequency operation and undesirable speed overshoots. To address these challenges and enhance overall motor control, this article introduces a new approach based on neural networks. Direct Torque Control method is specifically designed for Doubly Fed Induction Motors and utilizes an Artificial Neural Network. Unlike conventional methods, this approach eliminates the need for speed controllers, commutation tables, and hysteresis comparators, thus providing a more integrated and efficient solution. Simulations conducted in the Matlab/Simulink environment have demonstrated the significant advantages of this approach with a higher performance enhancement. Not only were torque ripples reduced, but speed overshoot was completely eliminated. Furthermore, significant reductions in Total Harmonic Distortion values of stator and rotor currents were achieved, indicating an overall improvement in system performance.

A novel direct torque control method for switched reluctance motors based on optimal turn-on angle

A novel direct torque control method for switched reluctance motors based on optimal turn-on angle

Direct Control Method for Linear-Rotary Switched Reluctance Motor With Two Radial Windings

For Linear-Rotary Switched Reluctance Motors (LRSRMs) with two radial windings, the coupling between torque and axial force increases the complexity of control. Due to the calculation of current in existing control method for LRSRMs, the complicated derivation of current expression was necessary, and some constraints were also introduced which meant the difficulties on designing the current control algorithm were greatly increased. In order to solve these problems, a direct torque and direct axial force (DTC&DAFC) control method is proposed in this paper. By the way of selecting appropriate space voltage vectors, the proposed method can directly regulate torque and axial force at the same time to achieve rotation and linear motion and significantly reduce the ripple of the torque. Moreover, the mechanism of two-DOF motion and the principle of the proposed method are demonstrated in detail based on a 6/4 LRSRM with two radial windings. Based on MATLAB/Simulink and the experimental prototype, the feasibility of the proposed control method has been verified according to the simulation and experimental results.

Explicit Model Predictive Cascade-Free Direct Force and Torque Control of Quadrotors

High-performance control of quadrotors' force and torques is the basis for achieving excellent trajectory tracking. However, the conventional method indirectly controls the force and torques by controlling four permanent magnet synchronous motors' speeds, resulting in poor dynamic performance and static deviations when pneumatic parameters mismatch. Dedicated to achieving high-dynamic and high-accuracy control of force and torques, an explicit model predictive (EMP) cascade-free direct force and torque control method is proposed. Firstly, defining force current and torque currents, whereby a new structure is proposed. Then, dynamics of the quadrotor and motor are fused to design the linear robust predictive models of force and torques. Accordingly, the EMP controller is constructed to replace the traditional cascaded speed solution module and four speed controllers uniformly. The EMP controller generates the optimal current commands directly from the force and torque commands, realizing direct control without the speed loop. The new structure makes it possible to solve the pneumatic parameter mismatch problem with an auxiliary extended state observer, obtaining offset-free control. The proposed method optimizes the dynamic performance and steady-state accuracy of force and torques and improves the system's robustness. Finally, the proposed method's feasibility is verified by experiments.

Design and Simulation Control Speed of Brushless DC 7 HP Using Direct Torque Method with Ripple Suppression

The last decade, electric cars have grown so rapidly. One of the driving parts in electric cars is the Brushless DC Motor (BLDC). The use of BLDC motors is needed because this motor has low mechanical losses, this is because the motor does not use brushes. However, in operation, there is still a ripple that is complained by the control or drive of the motor so that the efficiency of the motor rotation output torque and speed is not perfect. One way to operate a BLDC motor is by direct torque control method. The Direct Torque Control method became popular for controlling BLDC motors because it provides a fast dynamic torque response, the variables controlled in this DTC are flux and torque. Direct torque control (DTC) is a method used to control torque and speed on a motor with a variable frequency drive (VFD). This method is a calculation that includes estimating motor flux and torque based on the voltage and current on the stator. In the stator, the flux is estimated based on the stator voltage while the torque is estimated from the stator flux estimator and motor current.The input values measured to the DTC control are the current and voltage of the motor. The torque output of this DTC has a fairly high ripple along with the application of a larger load so that changes in motor load affect ωr. Ripple Torque that affects the speed of the rotor must be given an additional circuit, namely Ripple Suppression. This additional circuit will suppress the ripple so that the torque and speed rotation of the BLDC motor will be better. Therefore, this research will discuss the design and simula tion of the BLDC motor using the direct torque control method with ripple suppression which is expected to produce more efficient output from the BLDC motor due to the torque ripples on the motor have been reduced by the ripple suppression circuit. From the research results, it can be seen that the efficiency of BLDC motors increases by 2 to 3 percent at starting time and increases by around 1.5 percent at steady state.

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.

Speed Control of Induction Motor using Fuzzy Logic

Abstract: In this paper, speed control of induction motor using fuzzy logic controller is proposed. Speed control of induction motor takes place by, Direct torque control(DTC) method i.e. by directly controlling torque. Here we have used Voltage/Frequency speed control method of induction motor. The fuzzy logic controller (FLC) solves the problem of non linearity’s and parameter variation of induction motor. Unlike the conventional standard controllers, the proposed controller has much less computationally demanding. Direct torque control scheme of induction motor is firstly used. Then, the specified rule and their membership functions of proposed fuzzy logic system will be represented. The performance of a controller is evaluated under various operating conditions. A simplified FLC with relatively fewer rules will be implemented for perfect speed control.

A Direct Torque Control Method for CSC Based PMSG Wind Energy Conversion Systems

The Current Source Converter (CSC) technology is well suited for high power wind energy applications. Because it drives generally features like simple converter structure, smooth power injection at the grid side and excellent short circuit protection. The main drawback lays its dynamic torque response. An improved Direct Torque Control (DTC) method is proposed in this paper to overcome this drawback. Using DTC method for Permanent Magnet Synchronous Generators (PMSG) in a wind energy system has some advantages such as, simple control system and topology, ease of tracing Maximum available power from the wind and flux weakening control in high wind speeds. The simulation results demonstrate the effectiveness of the proposed control system, good dynamic response and acceptable MPPT capability.

Torque Ripple Reduction of BLDC Motor with a Low-Cost Fast-Response Direct DC-Link Current Control

In this study, a new low-cost direct DC-link current control (DDLCC) is proposed for the brushless direct current (BLDC) motors. The newly proposed DDLCC method has a fast dynamic torque response analogous to the direct torque control (DTC) method. Additionally, torque ripple reduction between two consequent commutations, the standstill and low-speed operation, the low-cost drive, and the reliability enhancement are provided by the proposed DDLCC method compared with the DTC method. Transferring the motor variables to the stationary or synchronous reference frame, which leads to having a high computational burden, is not required in this method. A simple derivative-based (SDB) method is proposed as well to provide the torque ripple without its DC offset value. The commutation interval is easily detected by a two-level hysteresis controller, and the commutation torque ripple is suppressed by applying the appropriate voltage vectors. Both the DDLCC and SDB methods are analyzed and then compared with some of the available DTC methods. Finally, the validity and performance of all analyzed methods are appraised by simulation and experimental results.

Direct electromagnetic force control of linear induction motor with end effects using fuzzy controller

In this article is a present dynamic model of a linen induction motor with end effects, occurs when the electromagnetic system of the motor is open. Instead of the angular speed and electromagnetic torque as a rotation motor, in the linear induction motor we have linear speed and linear electromagnetic force, which are sufficiently influenced by the open electromagnetic system of the primary and secondary elements of the linear motor. The choice of an appropriate control system for a linear induction motor is of particular importance considering the use of this type of motor in manufacturing. There are different types of control schemes for standard rotary motors that have their own advantages and disadvantages. When choosing a motor control scheme, we strive to achieve the following parameters, such as smoothness of regulation, ability to regulate in all four quadrants, accuracy of regulation, range of regulation and last but not least, simplicity of regulation. One such method that meets these criteria for rotary motors is the direct torque control method with space vector modulation. The control system of the linear induction motor proposed in this paper is based on this method, taking into account the open electromagnetic system and the occurrence of the end effects of the linear induction motor. Instead of the angular reference velocity as a rotary motor, in this case we have a linear reference velocity to the input, which is compared to the current linear velocity of the motor. The present paper also uses the vector modulation method by analogy with direct torque control with space vector modulation of the rotary motor. For the conversion of a linear velocity to a linear electromagnetic force, instead of a standard PI controller, it is using a fuzzy controller to convert a linear velocity to a reference electromagnetic force.

Effectiveness of Field Oriented Control and Direct Torque Control Methods for Induction Motor Speed Regulation

Induction motors are used extensively in many sectors, including manufacturing, power generation, healthcare, and transportation. Robust speed regulation of inductor motors is a key requirement for ensuring their intended usage and increasing their effectiveness. This study analyzes two advanced and popular methods for regulating the torque and speed of induction motors, namely, field-oriented control (FOC) and direct torque control (DTC). Detailed mathematical modeling of both methods is described, providing the in-depth perspective of the control algorithms and problem variables. This is followed by a thorough analysis of the performance of the control methods. Different control scenarios have been analyzed using simulation with MATLAB Simulink under different speed and loading conditions. The outcomes show that FOC provides better performance in terms of reduced torque jitter, smooth torque, and speed tracking response for highly variable load and reference speed profiles. Further, the FOC is found to generate better current waveforms. This leads to improving the power factor, decreasing electrical noise, and enhancing the motor performance. Meanwhile, the DTC demonstrates a strong capability to handle large speed changes and provide faster torque response, but it suffers from considerable torque variation. The simulation outcomes also suggest that the method selected to tune PI controllers is effective. The findings contribute to enhancing the efficient operation of induction motors and fostering their applications in diverse sectors for improved productivity and service, and superior economic gain.

Artificial intelligence-enhanced DTC command methods used for a four-wheel-drive system

This paper presents an artificial intelligence direct torque control (DTC) method for an electric vehicle (EV) drive system. The architecture of the proposed electric vehicle is that of four wheels each with an induction motor (IM). A comparative study of the different torque and speed controllers proposed in this paper is made. An electronic differential is used to control the speed of each wheel as well as a variable master-slave control (VMSC) for the management of the magnetic quantities because the motors on the same side are fed by the same converter. This study allows highlights the performance of the propulsion system in terms of dynamics and safety of the vehicle and better stability. The different controllers are implemented by the MATLAB/Simulink software and the simulation results obtained show better flexibility in the control of the vehicle. It is worth noting that direct torque control with fuzzy logic (DTFC) performs better than DTC associated with neural networks in terms of a time reduction increase of 1.47%, an overshoot of less than 5.33, and a static steady-state error close to zero.

Analysis of fuzzy and neural controllers in direct torque controlled synchronous motors

<p><span>In this study, multiple intelligent control systems for direct torque-controlled Synchronous motors are implemented and compared. Using a lookup table to pick a vector through the inverter voltage space, the direct torque control (DTC) system can be obtained. To replicate the state selector in relation to the look-up table, intelligent controllers are deployed. Intelligent logic controllers like fuzzy and neural are used to regulate the performance of permanent magnet synchronous motors (PMSM). In steady-state applications, neural and fuzzy controllers reduce the torque ripple and stator current harmonic distortion. These outcomes are compared with those obtained when the synchronous motor was put under the basic direct torque control method using a proportional integral (PI) controller. The accuracy and effectiveness of the suggested control topologies have been verified using computer simulation software like MATLAB/Simulink.</span></p>

Comparative Study of Electric Traction Control Techniques: Application to Motor Vehicles

Abstract: Climate change and evolution of technology have shown the important of electric vehicles (EV). Its performance strongly depends on the type of control techniques used to control their motor. In this paper, we compare the electric traction control techniques used in motor vehicles. We consider an electric vehicle with two driving wheels and we model it to bring out the mechanical, electrical and electromechanical equations. For our obtained road, we develop the control laws of our vehicle using Indirect Flux Oriented Control (IFOC) method, Direct Torque Control (DTC) method and Fuzzy DTC (DTFC) method. A comparative study of these control techniques is made using performance tools such as response-time, static error and ripple rate. Our study shows that DTFC method is better to obtain the motor instruction requested by the driver.