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This article starts from the premise that one of the global control strategies of the Permanent Magnet Synchronous Motor (PMSM), namely the Direct Torque Control (DTC) control strategy, is characterized by the fact that the internal flux and torque control loop usually uses ON–OFF controllers with hysteresis, which offer easy implementation and very short response times, but the oscillations introduced by them must be cancelled by the external speed loop controller. Typically, this is a PI speed controller, whose performance is good around global operating points and for relatively small variations in external parameters and disturbances, caused in particular by load torque variation. Exploiting the advantages of the DTC strategy, this article presents a way to improve the performance of the sensorless control system (SCS) of the PMSM using the Proportional Integrator (PI), PI Equilibrium Optimizer Algorithm (EOA), Fractional Order (FO) PI, Tilt Integral Derivative (TID) and FO Lead–Lag under constant flux conditions. Sliding Mode Control (SMC) and FOSMC are proposed under conditions where the flux is variable. The performance indicators of the control system are the usual ones: response time, settling time, overshoot, steady-state error and speed ripple, plus another one given by the fractal dimension (FD) of the PMSM rotor speed signal, and the hypothesis that the FD of the controlled signal is higher when the control system performs better is verified. The article also presents the basic equations of the PMSM, based on which the synthesis of integer and fractional controllers, the synthesis of an observer for estimating the PMSM rotor speed, electromagnetic torque and stator flux are presented. The comparison of the performance for the proposed control systems and the demonstration of the parametric robustness are performed by numerical simulations in Matlab/Simulink using Simscape Electrical and Fractional-Order Modelling and Control (FOMCON). Real-time control based on an embedded system using a TMS320F28379D controller demonstrates the good performance of the PMSM-SCS based on the DTC strategy in a complete Hardware-In-the-Loop (HIL) implementation. [ABSTRACT FROM AUTHOR]

This work is an overview of one of the renewable energy sources, wind power. The high cost of testing wind turbines and analyzing their characteristics in research laboratories prompted us to create the Wind Emulator. In this article, we will proceed with the development of an emulator of a wind turbine conversion chain based on an asynchronous machine. This emulator would be capable of faithfully reproducing the dynamic characteristics of a real wind turbine and of integrating them optimally into a real electrical system so as to be able to study its operation at laboratory level, so our objective is to have an emulator that will provide the characteristics (speed-torque-current) in real time and with realistic conditions. Our development approach is based on the use of two classical control strategies under the MATLAB/Simulink closed-loop environment: direct torque control (DTC) and indirect rotor flux vector control (IRFOC) in dynamic and static regimes. The simulation results presented and discussed in this work enable us to determine the operating limits of our proposed wind emulator, in order to validate the most suitable emulator model. Ultimately, this model will be integrated into an intelligent computing board such as the DSP1104. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Direct torque control is the most appropriate strategy for induction motor drive systems due to its considerable ability to reduce the impact of machine parameter variations while offering fast dynamic response and simplified control implementation. However, persistent problems associated with high torque ripples and variable switching frequencies prevent its widespread adoption. To overcome these limitations, several techniques have been developed, in particular the use of multi-level inverters and fuzzy logic algorithms. This article proposes an in-depth evaluation of these techniques in a MATLAB/Simulink environment under various operational conditions. The main objective is to provide a detailed performance analysis of these approaches, examining their effectiveness in torque and flux ripple reduction, switching frequency management, robustness, computation time, cost, current harmonic distortion, and algorithm complexity. These results will help to select the most appropriate control strategy for specific applications. [ABSTRACT FROM AUTHOR]

In view of the disadvantages of negative torque and low operation efficiency in the traditional direct torque control (DTC) for the switched reluctance motor drive (SRD), a novel DTC strategy based on optimal turn-on angle is proposed in this paper. First, the flux hysteresis controller of the traditional DTC is cancelled and the SRM is only controlled by the torque hysteresis controller. The actual rotor position angle is used to divide the sectors instead of the angle calculated by the stator flux, which does not need to select the optimal given flux value, and makes the division of sectors more in line with the inductance characteristics of the SRM. Second, the function for calculating the optimal turn-on angle is designed and the sectors are reallocated. The optimal voltage vector is selected according to the output signal of the torque hysteresis controller and sector position. Finally, the 12-sector DTC method is selected as comparison algorithm and the correctness of the proposed method is confirmed by simulation and experimental results. It is demonstrated that the proposed strategy retains the advantages of the simple structure of the traditional DTC. In addition, it eliminates negative torque, improves the DC bus voltage utilization and torque ampere ratio, and reduces the torque ripple, switching frequency and copper losses. [ABSTRACT FROM AUTHOR]

The torque ripple (TR) causes vibration in induction motor's shaft. This TR should be reduced to operate the induction motor drive safely. In this paper the modified torque comparator in direct torque control (DTC) scheme for three-phase induction motor is proposed to reduce the TR. The induction motor is fed with three-level neutral-point clamped (TLNPC) inverter so that the inverter gives more voltage vectors (VVs) as that of two level inverter. Due to the availability of more VVs, the DTC scheme can be implemented with modified five-level torque comparator (MFLTC). The MFLTC modifies the selection of VVs in a comparator both during incrementing and decrementing TR. The selection of VVs through MFLTC restricts the TR near the reference electromagnetic torque. The proposed DTC scheme also balances the dc link neutral point through alternately selection of positive and negative half VVs through MFLTC. To validate the proposed DTC method the simulation and experimental results are provided. [ABSTRACT FROM AUTHOR]

In recent scenarios, induction motors are used in many different fields due to their small size, advanced technology, and capacity to handle large amounts of power. One of the annoying downsides of conventional AC traction drive systems is the engine's speed and the uncertainty of the ripple content. The goal of the proposed work is to use various control techniques to analyze and enhance the performance of two five-phase induction motors that are supplied in parallel via an inverter. The control techniques are scalar control, six-step voltage type source inverter (VSI), space vector modulation (SVM) based VSI inverter, field-oriented control, model reference adaptive system-based field-oriented control (FOC), direct torque control (DTC), direct torque control -SVM, model reference adaptive system based direct torque control-SVM for traction application. The modified space vector modulation-based induction motor (IM) sensorless drive is realized together with a comparison of several control strategies. It makes use of direct torque control approaches with a model reference adaptive system (MRAS). An IM is designed, and performances are analyzed in high-speed and low-speed regions. Two bogies sets were considered in the closed-loop scheme, tested under parameter variations and in low-speed areas. The simulation result examined the most significant control methods for an IM fed by an inverter for electric traction applications. The performance of the torque in terms of reduced torque ripple in the IM drive is analyzed. The proposed direct torque control technique will reduce torque harmonic ripple by 100 % under the steady-state condition. Under a change in a parameter, the torque harmonic ripple is decreased by 99 %. For the IM drive, the hardware implementation of the advanced control approaches is examined.

Abstract The magnet-less switched reluctance motor (SRM) speed-torque characteristics are ideally suited for traction motor drive characteristics and its advantage to minimize the overall cost of on-road EVs. The main drawbacks are torque and flux ripple, which have produced high in low-speed operation. However, the emerging direct torque control (DTC) operated magnitude flux and torque estimation with voltage vectors (VVs) gives high torque ripples due to the selection of effective switching states and sector partition accuracy. On the other hand, the existing model predictive control (MPC) with multiple objective and optimization weighting factors produces high torque ripples due to the system dynamics and constraints. Therefore, existing DTC and MPC can result in high torque ripples. This paper proposed a finite set (FS)-MPC with a single cost function objective without weighting factor: the predicted torque considered to evaluate VVs to minimize the ripples further. The selected optimal VV minimizes the SRM drive torque and flux ripples in steady and dynamic state behaviour. The classical DTC and proposed model were developed, and simulation results were verified using MATLAB/Simulink. The proposed model operated in SRM drives experimental results to prove the effective minimization of torque and flux ripples compared to the existing DTC.

Abstract Enhancing the efficiency of the electric vehicle’s powertrain becomes a crucial focus, wherein the control system for the traction motor plays a significant role. This paper presents a novel electric vehicle traction motor control system based on a robust predictive direct torque control approach, an improved version of the conventional DTC, where the traditional switching table and the hysteresis regulators are substituted with a predictive block based on an optimization algorithm. Additionally, a robust predictive speed loop regulator is employed instead of the proportional-integral regulator, which integrates a new cost function with a finite horizon, incorporating integral action into the control law based on a Taylor series expansion. This technique’s primary benefit is its independence from the necessity to measure and observe external disturbances, as well as uncertainties related to parameters. The effectiveness of the suggested system was confirmed through simulation and experimental results under the OPAL-RT platform. The findings indicate that the proposed approach outperforms the conventional method in terms of rejecting disturbances, exhibiting robustness to variations in parameters, and minimizing torque ripple.

The direct torque control (DTC) strategy was proposed more than 25 years ago. It is one of the most successful and reliable techniques for AC motors. This paper presents the application of DTC using a four-switch inverter, as one of the non-conventional economic topologies suitable for low power ranges. The experimental prototype proves the validity and effectiveness of the investigated configuration. In addition, for comparison purposes, the DTC technique has been implemented using a conventional six-switch inverter. According to the experimental results, the DTC-based four-switch inverter would be competitive with the conventional topology in low power ranges to achieve an economic AC drive with a satisfactory transient and steady-state performance at moderate costs.

The magnet-less switched reluctance motor (SRM) speed-torque characteristics are ideally suited for traction motor drive characteristics and its advantage to minimize the overall cost of on-road EVs. The main drawbacks are torque and flux ripple, which have produced high in low-speed operation. However, the emerging direct torque control (DTC) operated magnitude flux and torque estimation with voltage vectors (VVs) gives high torque ripples due to the selection of effective switching states and sector partition accuracy. On the other hand, the existing model predictive control (MPC) with multiple objective and optimization weighting factors produces high torque ripples due to the system dynamics and constraints. Therefore, existing DTC and MPC can result in high torque ripples. This paper proposed a finite set (FS)-MPC with a single cost function objective without weighting factor: the predicted torque considered to evaluate VVs to minimize the ripples further. The selected optimal VV minimizes the SRM drive torque and flux ripples in steady and dynamic state behaviour. The classical DTC and proposed model were developed, and simulation results were verified using MATLAB/Simulink. The proposed model operated in SRM drives experimental results to prove the effective minimization of torque and flux ripples compared to the existing DTC. [ABSTRACT FROM AUTHOR]

Summary: The switched reluctance motor (SRM) is a prominent electrical machine drive with low cost and good performance in different drive applications. This machine's main drawbacks are torque ripple and flux ripple. However, the existing SRM‐operated direct torque control (DTC) Voltage vectors (VVs) give high torque ripples due to improper sector division and minimum selection of VVs switching states. On the other hand, a two‐level hysteresis torque band can result in torque ripples. Therefore, this paper proposed DTC using 16 partitions, active small and large VVs, and a multilevel hysteresis torque band (MHTB) strategy to mitigate the torque ripple further. More active VVs (i.e., 16) are employed in the modified sector‐based switching tables, suppressing the torque ripples. The proposed strategy is verified and validated using MATLAB/Simulink. The detailed result discusses the response of torque, flux, and speed of SRM. The DTC‐operated SRM drive experimental results prove the effective minimization of torque ripples in the proposed DTC compared to the existing DTC. [ABSTRACT FROM AUTHOR]

Direct torque control (DTC) based on sliding mode control (SMC) has been widely applied to permanent magnet synchronous motor (PMSM) drives for torque ripple reduction and flux tracking. However, the control performance may be degraded due to disturbances such as variations in motor parameters or uncertainties. In this paper, a DTC strategy with an improved composite SMC controller is proposed for the PMSM drive system to enhance its performance under various disturbances. The speed controller is first designed based on a proposed adaptive reaching law (ARL) to eliminate chattering that appears in the conventional SMC, accelerate convergence, improve tracking performance, and reduce torque ripples. Then, an enhanced extended sliding mode disturbance observer (E2SMDO) is developed to estimate the lumped disturbances of the PMSM drive system in real time and compensate for a feedforward to the speed controller. By combining the ARL and E2SMDO, a composite controller (denoted ARL + E2SMDO) is established, whose stability is proven through the Lyapunov theory. The effectiveness of the proposed method is validated by simulations and experiments. The results of both simulations and experiments demonstrate that the composite ARL + E2SMDO controller has a fast dynamic response, reduced torque ripples, strong robustness, and good anti‐disturbance compared to other conventional methods. [ABSTRACT FROM AUTHOR]

In this paper, robust predictive control (RPC) based on direct torque control space vector modulation (DTC-SVM) of the doubly fed induction generator wind turbine system (DFIG-WTS) is investigated to improve energy capture effectiveness. A novel cost function is introduced for the predictive speed regulator where the aerodynamic torque is considered as an unknown perturbation. This technique is designed to improve dynamic performance such as reference tracking, disturbance rejection, and robustness to parameter variations. The use of the DTC-SVM technique enhances performance in terms of constant switching frequency and reduced torque-flux ripples. The simulation results using real-time MATLAB/Simulink demonstrate the feasibility and validity of the proposed strategy, where very satisfactory performance has been achieved. [ABSTRACT FROM AUTHOR]

In the existing literature, direct torque control (DTC) by synthesizing virtual vectors can effectively suppress low-order harmonic currents under the single open-phase fault (OPF) of the five-phase permanent magnet synchronous motor (PMSM), but the sectors and the look-up tables need to be redesigned, which makes the control process more complicated. In order to solve this problem, an indirect correction method of virtual vectors is proposed, and the amplitudes of the virtual vectors are maximized. The fault-tolerant DTC strategy under the OPF ensures that there is no need to re-divide the sectors under the fault. And the selection rules of the look-up tables are consistent with the healthy operation. The difference is that the amplitudes of ten virtual vectors in the faulty operation are reduced, which simplifies the control process and is easy to implement. Finally, the correctness and effectiveness of the proposed control strategy were verified by experiments. [ABSTRACT FROM AUTHOR]

Increasingly, electricity network managers, through their grid codes, require renewable energy production systems to participate in system services, which includes requirements such as the stability of these production systems, the quality of the energy injected into the networks, the ability to withstand voltage dips, etc. To meet these requirements, the use of appropriate commands for the control of the production systems is necessary. Various control methods have been proposed, among which direct torque control (DTC) stands out. However, several studies have highlighted the impact of parametric variations on this control method. The contribution of the work presented in this article is the improvement of DTC when combined with a fuzzy estimate applied to a wind production system based on an asynchronous machine. Robustness tests were simulated to highlight the sensitivity of this control to variations in the stator resistance of asynchronous machines. To make this command robust and stable, a fuzzy estimator was used with this command. The simulation results demonstrated that this combination (DTC with a fuzzy estimator) makes the wind system more stable. To assess the effectiveness of the proposed solution, the root mean square error index was used. [ABSTRACT FROM AUTHOR]

In this paper, a reference stator flux linkage calculation method is proposed for realizing maximum efficiency operation in direct‐torque‐controlled interior permanent magnet synchronous motor (IPMSM) drives. The proposed method is based on the solutions of a quartic equation, a motor model in the d‐q rotating frame widely used for synchronous motor controllers, and a well‐known equation for maximum efficiency operation. Therefore, the proposed method uses neither any approximation function nor any look‐up table that depends on the parameters of the motor, which has to be created in advance. Simulation results validate that the proposed methods can achieve maximum efficiency operation in IPMSM drives. [ABSTRACT FROM AUTHOR]

The variable DC link direct torque control (DTC) for induction motors was proposed in this paper utilizing an artificial neural network (ANN). Variable DC-link voltage is utilized as the inverter's controlling input to improve the induction motor's performance. By injecting the dynamically variable dc-link voltage, inverter switching losses are decreased and inverter efficiency is increased. Two significant limitations are the torque ripple in DTC and the speed regulation of induction motors at low speeds. The driveline of an electric vehicle is modeled, and the suggested control is put into practice to enhance low-speed speed regulation, high dynamic performance, and minimal torque ripple. With variable DC-link voltage based on ANN, an improvement in torque and speed is made possible. Additionally, the suggested strategy minimizes the current ripples. To verify the improved efficacy of the electric driveline under various operating scenarios, a proposed control of the electric driveline is implemented using MATLAB SIMULINK, and the results are compared with the conventional scheme. The recommended speeds for the three speed ranges are as follows: 300 rpm for low speed, 900 rpm for medium speed, and 1275 rpm for high speed. The torque ripples decreased from 0.39 to 0.24 in the low-speed region, 0.38 to 0.24 in the medium-speed region, and 0.36 to 0.24 in the high-speed region while the motor was operated at a constant load torque of 2 N-m. The torque ripples decreased from 0.4 to 0.274 in the low speed region, 0.4 to 0.274 in the medium speed zone, and 0.2 to 0.274 in the medium speed region when the motor operated at various speed regions with a constant load. The main effect of running the motor at different load torques, such as 1.5 N-m, 2.5 N-m, and 2.0 N-m, is shown in Table 9 and numerical data of torque ripples is presented in Table 9. [ABSTRACT FROM AUTHOR]

The direct torque control (DTC) strategy was proposed more than 25 years ago. It is one of the most successful and reliable techniques for AC motors. This paper presents the application of DTC using a four-switch inverter, as one of the non-conventional economic topologies suitable for low power ranges. The experimental prototype proves the validity and effectiveness of the investigated configuration. In addition, for comparison purposes, the DTC technique has been implemented using a conventional six-switch inverter. According to the experimental results, the DTC-based four-switch inverter would be competitive with the conventional topology in low power ranges to achieve an economic AC drive with a satisfactory transient and steady-state performance at moderate costs. [ABSTRACT FROM AUTHOR]

Induction motors are used in a wide range of industrial applications, especially as variable speed drives and for motion control. These motors have complex dynamic performance and nonlinear characteristics. The torque ripples in steady state operation, particularly at low speeds limits their application. Although the field orientation control principle provides an effective algorithm but due to its complexity, a novel direct torque control (DTC) approach is proposed in this paper. The control approach's simplicity and novel control characteristics were minimally negatively affected by significant torque and flux ripples. There are a wide range of applications for space vector modulation with the proposed DTC approach. Though some of the drawbacks of the conventional DTC have been addressed, which include issues such as robustness to parameter variation and load disturbance still remain unresolved. As a result, to mitigate these disadvantages, sliding mode DTC was applied to an induction motor control to reduce torque ripple. Therefore, in this paper, a novel space vector modulation (SVM) based fractional order sliding mode control (FOSMC) of induction motor is proposed. For this purpose, a fractional order proportional integral sliding surface was designed. To improve the control performance of the system, the speed control loop was implemented using super twisting sliding mode control (SMC). Furthermore, to estimate the stator flux, torque, and flux angle, neural networks has been employed. The proposed controller's stability was examined using the Lyapunov stability analysis. The simulation results confirm the proposed control method's effectiveness and validity. The sliding mode torque (SMT) control and estimators were found to be unaffected by parameter variation and load disturbance. A super twisting algorithm-based speed SMC, in conjunction with a fractional order proportional integral sliding surface was found to effectively reduce the torque ripples. Furthermore, chattering was reduced by using a super twisting algorithm for speed control. The torque ripple band was modified by ±6 Nm using the fractional SMC and the flux ripple band was modified by ±0.04 Wb. [ABSTRACT FROM AUTHOR]

This paper introduces a novel direct torque control approach based on the decision tree (T-DTC), employing artificial neural networks that are effectively trained to enhance accuracy and robustness. The main objective of T-DTC is the substantial reduction of flux and torque ripples inherent in the conventional DTC, ensuring effective control of the induction motor. The conventional hysteresis controllers for stator flux and electromagnetic torque are replaced by two advanced controllers named M5 Prime model trees. Additionally, the traditional switching table is substituted with a novel decision tree table utilizing the classifier algorithm 4.5. The effectiveness of the proposed T-DTC strategy is demonstrated through simulation in MATLAB/Simulink and validated in real-time using an HIL platform based on OPAL-RT OP 5600 and Virtex 6 FPGA ML605. The results obtained demonstrate a notable improvement compared to existing techniques in the literature. [Display omitted] • An enhanced DTC strategy for induction motor based on decision tree is proposed. • A neural learning process is applied for the designed controllers. • Easy real-time implementation of the Tree-DTC strategy via the HIL tests is realized. • Considerable minimization of stator flux and electromagnetic torque ripples is achieved. • Robust Tree-DTC strategy in terms of speed monitoring and disturbance rejection is achieved. [ABSTRACT FROM AUTHOR]

In order to further reduce the torque, flux-linkage fluctuation, and current harmonic content of dual three-phase permanent magnet synchronous motors, this paper proposes a direct torque control strategy combined with a master–slave virtual vector duty cycle assignment. Two types of virtual voltage vectors with different amplitudes are used to form a harmonic suppression switching table. The virtual vectors are classified into master and slave virtual vectors according to the degree of influence on the torque and the flux-linkage. Then, the duty cycle of the master and slave virtual vectors is recalculated and allocated through the evaluation function to achieve accurate control of the torque and the flux-linkage. Finally, the switching sequences of the master and slave virtual vectors that act together in one control cycle are rearranged into a symmetrical waveform. It is experimentally verified that the phase current THD of the proposed strategy is reduced by 69.4%, the 5th and 7th current harmonics content is significantly reduced, and the torque fluctuation and flux-linkage fluctuation can also be effectively suppressed, which provides better dynamic performance and steady-state performance. [ABSTRACT FROM AUTHOR]

Water pumping systems are crucial for extracting water from deep wells. However, electricity shortages and high fuel prices significantly impact the efficiency and reliability of these systems. Therefore, renewable energy sources have gained more attention as alternatives to fossil fuels. Photovoltaic (PV) energy-based pumping systems, in particular, are becoming popular, especially in rural areas where grid connections are often unavailable. Several factors influence the performance of photovoltaic water pumping systems (PVWPS), including solar irradiance, temperature, system design, maintenance, and pumping load. To ensure optimal performance under these varying conditions, two controllers are crucial. The first controller is the Maximum Power Point Tracking (MPPT) controller, designed to maximize power extraction from the PV panels under varying environmental conditions (in particular, solar radiation and temperature). The second controller regulates the speed and torque of the induction motor (IM) which drives the pump responsible for water extraction. Therefore, to improve the performance of these controllers under different conditions. This review paper first examines widely used soft computing methods, providing a detailed description of each. These methods are then applied to both the MPPT and the IM controllers, offering valuable insights for researchers looking to develop advanced PVWPS control configurations for future applications.

Abstract High performance and comfort are key features recommended in hybrid electric vehicle (HEV) design. In this paper, a new coordination strategy is proposed to solve the issue of undesired torque jerks and large power ripples noticed respectively during drive mode commutations and power sources switching. The proposed coordinated switching strategy uses stair-based transition function to perform drive mode commutations and power source switching’s within defined transition periods fitting the transient dynamics of power sources and traction machines. The proposed technique is applied on a battery/ supercapacitor electric vehicle whose traction is ensured by two permanent magnet synchronous machines controlled using direct torque control and linked to HEV front and rear wheels. Simulation results highlight that the proposed coordinated switching strategy has a noteworthy positive impact on enhancing HEV transient performance as DC bus fluctuations were reduced to a narrow band of 6 V and transient torque ripples were almost suppressed.

Variation in switching frequency with operating speed and high torque ripples are two important limitations of the Direct Torque Control or DTC technique. The potentiality of the switching device cannot be fully exploited for variable switching frequency (in the case of lowest frequency) whereas high torque ripples lead to vibrations and acoustic noise in the motor. A five-phase induction motor (FPIM) based on DTC technique is presented here to overcome these drawbacks. A five-level Proportional-Integral (PI) based torque controller using waveform comparison is employed in the drive. The PI controller will process the torque error whose output is then compared simultaneously with four constant frequency triangular waves to achieve constant switching frequency. The gains of PI controller are designed using linear control theory for minimum torque ripples. Stator current distortion due to the presence of auxiliary subspace in the five-phase system is also minimized. The demagnetization of stator flux during low-speed operation is mitigated through the selection of voltage vectors that are present thirty-six degrees within the sector boundaries. Experimental results have been presented for validating the steady state and dynamic performance of proposed DTC technique.

This paper aims to design a controller for a matrix converter fed induction motor drive providing less torque ripples and eliminating peak overshoots with good transient and steady state responses utilizing fuzzy and direct torque control. The proposed controller utilizes Direct Torque Control (DTC) strategy with space vector modulation for regulating stator flux and electromagnetic torque. Due to the superior control capabilities of the matrix converter such as bidirectional power flow, sinusoidal input/output waveforms, high power density and lesser volume, it has attracted significant research interest in the field of adjustable speed drive. Hence the proposed matrix converter based controller is developed in MATLAB/Simulink and tested in different input/output conditions. To validate simulation results, a laboratory prototype is built around the Altium Nano Board 3000 equipped with a Xilinx Spartan using Field Programmable Gate Array (FPGA) is employed. The proposed control scheme, validated through simulation and hardware testing, ensures stable, robust drive system with significant reductions in input side harmonics and enhances induction motor drive's performance.

A hybrid technique is proposed in this manuscript for the optimal design of an induction motor (IM) drive for the dynamic load profiles during torque and flux control. The proposed hybrid method combines a Ladder-Spherical-Evolution-Search-Algorithm (LSE) and a recalling-enhanced recurrent-neural network (RERNN), which is called an LSE-RERNN technique. The major objective of the proposed method is to minimize IM losses while maintaining control over speed and torque. The proposed method effectively tunes the gain parameter of the PI controller for flux and torque regulation. The LSE methodgenerates a set of gain parameters optimally predicted by RERNN. The method reduces losses without prior knowledge of load profiles, achieving energy savings for steady-state optimum flux. The performance of the proposed technique is done in the MATLAB and is compared with different existing techniques. The value of the proposed method for the mean is 0.328, the standard deviation (SD) is 0.00334, and the median is 0.4173. The loss of the proposed method is much less than 0.3 W while compared to different existing approaches. Moreover, the computation time of the proposed approach is lesser than the existing techniques. • Optimal design of IM drive to control the torque and flux. • The proposed method is reducing the loss of IM. • LSE is utilized to generate the set of gain parameter. • The proposed technique is implemented in the MATLAB. • The computation time of the proposed method is lesser. [ABSTRACT FROM AUTHOR]

In an age characterized by a focus on environmental sustainability and technological advancement, the creation and integration of hybrid electric vehicles (HEVs) have become a significant solution in the realm of transportation and clean energy. This study introduces a method for optimizing the distribution of torque in HEVs through the utilization of artificial neural networks (ANN). Furthermore, it introduces an innovative design for the vehicle's drivetrain, enabling it to function in both rear-wheel and four-wheel drive configurations. The HEV is propelled by a permanent magnet synchronous machine (PMSM) and is controlled using direct torque control (DTC) due to its capability to provide rapid and precise responses. The results of simulations conducted using MATLAB/Simulink confirm the effectiveness of the proposed intelligent torque distribution strategy, demonstrating its capacity to enhance vehicle performance, driving comfort, and propulsion power. [ABSTRACT FROM AUTHOR]

Switched reluctance motors (SMRs) are competitors of traditional ones in electric vehicles due to their high specific performance and the absence of permanent magnets and windings in the rotor design, which increases reliability and reduces production costs. Due to the pronounced nonlinearity of their magnetic characteristics and discreteness in control, SRMs are characterized by significant torque ripples, noise, and vibrations, to suppress which it is advisable to use direct instantaneous torque control (DITC), which is widely used in traditional electric drives. However, SRMs differ from traditional motors, so known technical solutions cannot be applied to them. Simulation modeling is a convenient and universal tool for research and development of methods and algorithms for SRM control, and the MATLAB/Simulink environment makes it possible to successfully implement them. The article considers two of the best-known and fundamentally different DITC options with respect to a four-phase SRM. Their shortcomings are substantiated and illustrated, and a new DITC option is proposed that is most suitable for controlling an SRM as part of a traction electric drive of electric vehicles. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) water pumping systems address water accessibility challenges in isolated regions by offering sustainable, self-sufficient solutions that do not rely on the power grid. These systems provide enduring advantages, such as reduced operational expenses, while also making a substantial contribution to agricultural progress and enhancing the quality of life in rural areas. The utilization of solar energy for powering rural areas has been significantly reduced due to recent technological breakthroughs. The objective of this study was to utilize MATLAB-Simulink models to simulate a photovoltaic water pumping system and generate an ideal direct current (DC) voltage at the input of the inverter. In addition, the machine side utilizes space vector modulation (DTC-SVM), while the DC voltage side employs fuzzy logic control (FLC). The fuzzy logic methodology is highly effective in dealing with non-linear and complicated systems, providing strong control in situations where conventional methods may face difficulties. DTC-SVM improves the management of motors by providing superior dynamic performance, minimizing torque fluctuations, and increasing overall efficiency. This makes it a highly valuable technique for motor control systems. When the DTC-SVM method is applied to the induction motor instead of the field-oriented control (FOC) and conventional direct torque control (DTC), it was discovered that the centrifugal pump exhibits a more rapid dynamic reaction and performs more effectively. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Controlling the speed and torque of electric vehicles (EVs) under various road conditions poses a significant challenge with conventional control methods. This paper introduces a novel approach to direct torque control (DTC) by incorporating a self-tuning fuzzy speed controller specifically designed for EV applications. The self-tuning fuzzy proportional-integral-derivative (PID) controller is devised to continually update its output scaling factor. DTC, which directly links torque and speed control to the electromagnetic state of the motor, eliminates the need for a modulator. It performs effectively at high speeds and operates without a speed sensor. However, DTC is typically employed in the medium and low-speed range of electric vehicle propulsion. This paper aims to develop a DTC structure utilizing a self-tuning fuzzy speed controller for driving a fuel cell electric vehicle in low-speed urban scenarios. Simulation results demonstrate that the adaptive fuzzy PI control ensures better efficiency compared to the conventional PI controller, affirming its superior control performance.

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.

Electric vehicles (EVs) are unquestionably the future of transportation due to their numerous advantages, such as their ability to address environmental issues, decrease dependence on fossil fuel, and enhance energy security. Attaining optimum performance, efficiency, and safety in EVs requires accurate control over both the speed and torque of the electric motor used. The Doubly Fed Induction Motor (DFIM) is classified as a motor that offers precise control over both its speed and torque. Additionally, it has some features that render it suitable for EV applications. This study contributes to advancing the field of new control systems for a DFIM used in EV applications. A key novelty of this work is the introduction of the Backstepping-Direct Torque Control (BSC-DTC) system for DFIM in EV applications. The suggested controller accurately tracks the specified speed set by the EV driver (reference speed) without any deviation, which is a key characteristic in modern EVs. Furthermore, the torque of the DFIM is regulated using the developed DTC method, BSC-DTC. To assess the capability of the BSC-DTC to effectively monitor the reference speed and achieve torque control, a comparison with conventional DTC is provided. Furthermore, an experimental implementation was conducted using the DS1104 board developed by dSPACE to validate the simulation results, highlighting the practical feasibility of the proposed system. Comprehensive modeling of the EV drivetrain was conducted and simulated utilizing the MATLAB-Simulink environment. The simulation findings demonstrate that the suggested control system offers superior performance for the EV system in terms of accurate reference speed tracking with zero tracking error and a slight overshoot of 0.1 km/h, as well as dynamic torque response. However, ripples in the electromagnetic torque provided by the motor have been observed. To address this issue, another innovative aspect of the work involves focusing future efforts on implementing control approaches based on artificial intelligence methodologies, opening new research and innovation avenues.

Purposes To achieve stable and efficient energy storage in the new elastic potential energy storage system, it is first necessary to establish an accurate mathematical model to reveal the operating characteristics of the energy storage box, and complete the calculation and configuration model of its capacity and power; Second, a strong robust control algorithm is needed to achieve the fast torque response while effectively suppressing disturbances. Methods In this paper, an accurate mathematical model of the energy storage system was established. Combined with the backstepping control algorithm, the direct torque adaptive control method of the permanent magnet synchronous motor is designed, and a new robust control strategy for the energy storage process of the elastic potential energy storage system is formed. Conclusions Through experiments, it has been proven that this control strategy has a fast torque response speed and can quickly match the rapidly increasing reverse torque of the energy storage box with minimal pulsation. At the same time, it can effectively restrain the unique moment of inertia parameter disturbance of the energy storage system, and then achieve stable and efficient energy storage.

This paper presents a fractional-order adaptive mechanism-based model reference adaptive system (MRAS) configuration for speed estimation of sensorless direct torque control (DTC) of a five-phase induction motor. In effect, the fractional-order proportional-integral (FOPI) controller parameters are obtained by the particle swarm optimisation (PSO) algorithm to enhance the MRAS observer response. Thus, the developed algorithm in the speed loop control of the DTC strategy to increase its robustness against disturbances. Moreover, a comparative study has been done of the proposed MRAS-PSO/FOPI speed estimator with the conventional MRAS-proportional-integral (PI) and the PSO-based MRAS-PI. Simulation results have carried out of the different controllers used in the adaptation mechanism of the MRAS estimator, to show the performance and robustness of the proposed MRAS-PSO/FOPI algorithm in use.

In this study, a speed sensorless control method is proposed for a photovoltaic water-pump system operating under variable atmospheric conditions. The developed system not only continuously determines the maximum power point of the photovoltaic system but also generates a reference speed appropriate for each power value produced. The MATLAB/Simulink model of the driver system incorporates Adaptive Power Control, Direct Torque Control, a 3-phase induction motor, and the power plant. The determination of the maximum power point of the photovoltaic system and the input reference speed information for the Direct Torque Control under varying atmospheric conditions is accomplished through the application of the Adaptive Power Control algorithm. Notably, the control process operates as a closed-loop system without the requirement of a speed sensor. Instead, the Extended Kalman–Bucy estimator is employed for speed estimation. Empirical evaluation of the proposed method was conducted under constant temperature conditions and varying irradiance values. The results clearly illustrate the consistent operation of the motor, with a constant torque production aligned with each identified maximum power point corresponding to distinct irradiance levels. The control system demonstrates robust performance and operational efficiency across the entire range of operating points. The efficacy of the Kalman estimator in monitoring the reference speed, the utilization of a single solar radiation sensor, and the successful implementation of sensorless operation are significant advantages of the developed adaptive approach. The demonstrated performance of the proposed system showcases its potential for enhancing the efficient and reliable control of photovoltaic water-pump systems in real-world applications.

This article starts from the premise that one of the global control strategies of the Permanent Magnet Synchronous Motor (PMSM), namely the Direct Torque Control (DTC) control strategy, is characterized by the fact that the internal flux and torque control loop usually uses ON–OFF controllers with hysteresis, which offer easy implementation and very short response times, but the oscillations introduced by them must be cancelled by the external speed loop controller. Typically, this is a PI speed controller, whose performance is good around global operating points and for relatively small variations in external parameters and disturbances, caused in particular by load torque variation. Exploiting the advantages of the DTC strategy, this article presents a way to improve the performance of the sensorless control system (SCS) of the PMSM using the Proportional Integrator (PI), PI Equilibrium Optimizer Algorithm (EOA), Fractional Order (FO) PI, Tilt Integral Derivative (TID) and FO Lead–Lag under constant flux conditions. Sliding Mode Control (SMC) and FOSMC are proposed under conditions where the flux is variable. The performance indicators of the control system are the usual ones: response time, settling time, overshoot, steady-state error and speed ripple, plus another one given by the fractal dimension (FD) of the PMSM rotor speed signal, and the hypothesis that the FD of the controlled signal is higher when the control system performs better is verified. The article also presents the basic equations of the PMSM, based on which the synthesis of integer and fractional controllers, the synthesis of an observer for estimating the PMSM rotor speed, electromagnetic torque and stator flux are presented. The comparison of the performance for the proposed control systems and the demonstration of the parametric robustness are performed by numerical simulations in Matlab/Simulink using Simscape Electrical and Fractional-Order Modelling and Control (FOMCON). Real-time control based on an embedded system using a TMS320F28379D controller demonstrates the good performance of the PMSM-SCS based on the DTC strategy in a complete Hardware-In-the-Loop (HIL) implementation.

Introduction. The best way to control the torque of an induction motor is conventional direct torque control (DTC); this control method is the most used approach in the industrial sector due to its many advantages. Its main advantages are its simplicity and its exclusive dependence on the stator resistance of the induction motor. However, the use of hysteresis comparators reduces its effectiveness, causing more torque ripple. Additionally, this results in variable operating frequency and limited frequency sampling, resulting in pseudo-random overshoot of the hysteresis band. Purpose. For these reasons, this article presents a new study aimed at confirming its shortcomings and improving the effectiveness of the control. Novelty. We propose to use fuzzy logic methods to estimate the two components of the stator flux. Methods. In traditional DTC the flux components are estimated from an equation relating the stator resistance to the stator voltage and current. In the proposed method, only stator currents and voltages are used for this evaluation, which eliminates the dependence of DTC on stator resistance. The aim of this proposal is to make DTC robust to parametric changes. Results. General harmonic distortions, rotational speed of the induction motor, electromagnetic moment, magnetic flux and stator currents are analyzed. Practical value. With this proposed technique, validated in Simulink/MATLAB, several improvements in motor behavior and control are endorsed: torque fluctuations are reduced, overshoot is completely eliminated, and total harmonic distortion is significantly reduced by 48.31 % for stator currents. This study also confirmed the robustness of DTC to changes in stator resistance. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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Introduction. The best way to control the torque of an induction motor is conventional direct torque control (DTC); this control method is the most used approach in the industrial sector due to its many advantages. Its main advantages are its simplicity and its exclusive dependence on the stator resistance of the induction motor. However, the use of hysteresis comparators reduces its effectiveness, causing more torque ripple. Additionally, this results in variable operating frequency and limited frequency sampling, resulting in pseudo-random overshoot of the hysteresis band. Purpose. For these reasons, this article presents a new study aimed at confirming its shortcomings and improving the effectiveness of the control. Novelty. We propose to use fuzzy logic methods to estimate the two components of the stator flux. Methods. In traditional DTC the flux components are estimated from an equation relating the stator resistance to the stator voltage and current. In the proposed method, only stator currents and voltages are used for this evaluation, which eliminates the dependence of DTC on stator resistance. The aim of this proposal is to make DTC robust to parametric changes. Results. General harmonic distortions, rotational speed of the induction motor, electromagnetic moment, magnetic flux and stator currents are analyzed. Practical value. With this proposed technique, validated in Simulink/MATLAB, several improvements in motor behavior and control are endorsed: torque fluctuations are reduced, overshoot is completely eliminated, and total harmonic distortion is significantly reduced by 48.31 % for stator currents. This study also confirmed the robustness of DTC to changes in stator resistance.

Abstract This paper establishes the torque equation of brushless doubly‐fed reluctance machines (BDFRMs) expressed by power winding or control winding (CW) flux vectors and the defined flux vectors generated by magnetic field modulation. On this basis, the direct torque control theory of BDFRM is established. The derivative expression of torque and CW flux are derived for accurately analysing the effect of CW voltage vectors and machine operation points on torque and CW flux. In addition, the space vector modulation‐based direct torque control strategy of BDFRM is proposed, which can keep the switching frequency constant. The two methods are compared and analysed through experimental results.

Increasingly, electricity network managers, through their grid codes, require renewable energy production systems to participate in system services, which includes requirements such as the stability of these production systems, the quality of the energy injected into the networks, the ability to withstand voltage dips, etc. To meet these requirements, the use of appropriate commands for the control of the production systems is necessary. Various control methods have been proposed, among which direct torque control (DTC) stands out. However, several studies have highlighted the impact of parametric variations on this control method. The contribution of the work presented in this article is the improvement of DTC when combined with a fuzzy estimate applied to a wind production system based on an asynchronous machine. Robustness tests were simulated to highlight the sensitivity of this control to variations in the stator resistance of asynchronous machines. To make this command robust and stable, a fuzzy estimator was used with this command. The simulation results demonstrated that this combination (DTC with a fuzzy estimator) makes the wind system more stable. To assess the effectiveness of the proposed solution, the root mean square error index was used.