Hysteresis Comparator 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.

Design of Pseudorandom Signal Generator Based on a Dual Memristor Chaotic System

This paper constructs a pseudo-random signal generator based on a dual memristor chaotic system. Firstly, the chaotic characteristics of the dual memristor chaotic system were explored through theoretical analysis and MATLAB numerical simulation, and a MULTISIM simulation circuit for the dual memristor chaotic system was constructed. Then, based on the threshold decision quantization method, a pseudorandom signal generator quantization circuit is formed by connecting an inverter amplifier and a hysteresis comparator on the output side of the analog circuit. Finally, the randomness of the pseudorandom sequence is discussed by NIST test and correlation analysis. The analysis results show that the pseudorandom sequence generated by the pseudo-random signal generator based on the dual memristor chaotic system exhibits good randomness.

Intelligent control of the power generation system using DSPACE

AbstractWind power systems (WPs) are complex non‐linear systems with varying parameters affected by environmental changes, including wind speed fluctuations. Extracting maximum power from WPs poses a significant challenge due to these factors. Direct power control (DPC) is a highly effective technique known for its simplicity and ease of implementation. However, it suffers from power ripples caused by the use of hysteresis comparators and switching tables that operate at variable frequencies. To address this issue, this paper presents the robust neural controller (NC) based on DPC, which replaces the switching tables. The Double‐Fed Induction Generator (DFIG) is the chosen generator for the studied WP system due to its advantageous features. The NC‐DPC effectively regulates the exchange of active and reactive powers between the DFIG and the system, maximizing power extraction from the WP system while reducing Total Harmonic Distortion and enhancing overall system quality. The effectiveness of the NC‐DPC is evaluated through MATLAB simulations and further supported by experimental data obtained using the Real‐Time Interface of the dSPACE‐DS1104 Controller card.

Artificial neural network-based direct power control to enhance the performance of a PMSG-wind energy conversion system under real wind speed and parameter uncertainties: An experimental validation

With the increasing emphasis on embedding advanced technology into system controls, the Direct Power Control (DPC) approach has garnered considerable attention due to its simple and highly adaptable algorithm. This approach has been increasingly recognized in numerous applications. However, the variable frequency, harmonic distortion of the currents, and power ripples caused by Hysteresis controllers and switching tables decrease its effectiveness and robustness, affecting the system’s performance. For this reason, this paper proposed a new DPC based on Artificial Neural Network (ANN) approaches. In this approach, the hysteresis comparator and the switching table are substituted with ANN controllers and then applied on both sides: machine-side converter (MSC) and grid-side converter (GSC) of a Permanent Magnet Synchronous Generator based Wind Energy Conversion System (PMSG-WECS). Moreover, to make the system more efficient in varying wind conditions, this study expands the utilization of the artificial neural networks (ANN) to encompass the maximum power point tracking (MPPT) control strategy. To demonstrate the effectiveness of the proposed approach on the system behaviors, a simulation test was carried out in the Matlab/Simulink environment, using a real wind profile of a Moroccan city (Essaouira). In comparison to the classical DPC control, the simulation results showed the superior performance of the proposed ANN-DPC control in terms of reference tracking, response time, overshoot, precision, and its capacity to reduce the rate of power ripples and total harmonic distortion (THD) in the injected currents. Furthermore, a robustness test was also included in this work to check the robustness of the proposed control against parameters variation. In conclusion, the feasibility and effectiveness of the ANN-DPC control approach were confirmed through experimental validation using the dSPACE DS1104 board.

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.

Safety hysteresis comparator design for transient overvoltage detection

This research introduces a safety hysteresis comparator that detects transient overvoltage in the track circuit relay interlocking of railway signaling system. This overvoltage is caused by voltage faults transmitted through the electric conductor on the track feed unit to the receiver equipped with the track relay, which acts as the occupied track circuit controller. The circuit was designed using safety system design principles and concepts. Findings illustrated that the transient overvoltage detection of the safety hysteresis comparator in the track circuit activated when the input voltage (Vin) was higher than the high hysteresis signal level (Vhyst_H). When Vin was less than low hysteresis signal level (VVhyst_L), the output voltage (Vo) state was low. Otherwise, it was high. The hysteresis voltage was 4.4 V. The installation of the transient overvoltage detector in the track circuit was to monitor the transient overvoltage fault in the track circuit and to confirm that the hysteresis comparator was in the safety failure mode, which was the safety function for the track circuit to be compliant with the IEC 61800-5-2 standard to ensure the system stability and reliability. It would maximize the performance of the controlling function and commanding of train arrangement of State Railway of Thailand (SRT).

Two different controllers-based DPC of the doubly-fed induction generator with real-time implementation on dSPACE 1104 controller board

The direct power command (DPC) of the doubly-fed induction generators (DFIG) has garnered increasing attention due to its simplicity, ease of implementation, and fast dynamic response that distinguished it from other controls. Recently, nonlinear controllers have been suggested to improve the DPC robustness, in particular the minimization of the DFIG power fluctuations. In the present research work, two different controls are used to regulate the DFIG power, where the first is a traditional DPC and the second is the DPC based on neural super-twisting algorithm (NSTA) controllers. The NSTA controllers were used instead of hysteresis comparators in the DPC technique, and the pulse width modulation (PWM) technique was used as a suitable solution instead of the switching table to better manage the state of switches and simplify the control system. The proposed controls were investigated and implemented using Matlab software and Dspace 1104 card with different tests to determine the best control. Experimental and simulation results show the good efficiency of the NSTA controller in improving energy and current quality. Also, the comparison is made between both techniques and the other controls in terms of reducing current harmonic distortions and ratios of the DFIG power fluctuations.

Comparing hysteresis comparator and RMS threshold methods for automatic single cough segmentations

Comparing hysteresis comparator and RMS threshold methods for automatic single cough segmentations

A Fault-Tolerant Control Strategy for Three-Level Grid-Connected NPC Inverters after Single-Arm Failure with Optimized SVPWM

Three-level NPC inverters have been widely used in grid-connected systems due to their superior performance compared with two-level inverters, but more switches lead to high fault probability. Meanwhile, the neutral point potential (NPP) fluctuation of the DC link is an inherent problem of three-level NPC inverters. To keep the three-level NPC inverter running stably after single-arm failure, a fault-tolerant control strategy based on an optimised space vector pulse width modulation (SVPWM) is proposed in this paper. Firstly, the common-mode voltage (CMV) of the postfault three-level NPC inverter is analysed and then the preliminary synthesis principles of the reference voltage vector are determined. Then, in order to ensure the NPP balance and the quality of the grid-connected currents, the reference voltage vector synthesis rules are optimised, a low-pass filter (LPF) and a hysteresis comparator are designed, respectively, to ensure the quality of grid-connected currents and effectively decrease the DC link NPP deviation. Finally, the simulation results show that the proposed fault-tolerant control strategy can realize the stable and reliable operation of the grid-connected three-level NPC inverter after single-arm failure, and the CMV can be reduced significantly, the quality of grid-connected currents is also improved. The proposed fault-tolerant strategy also shows good performance when the grid-connected currents change.

Frequency analysis of stator currents of an induction motor controlled by direct torque control associated with a fuzzy flux estimator

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.

Analysis of Direct Torque Control Response to Stator and Rotor Faults in Permanent Magnet Synchronous Machines

Direct-torque-control-driven permanent magnet synchronous machines eliminate the need for a position sensor while providing improved torque dynamics. However, the structure, regulation principle and nature of compensation of hysteresis-based controllers used in direct torque control impacts performance under faulty operating conditions. This paper analyzes the reaction of direct torque control to the presence of various faults that occur in permanent magnet synchronous machines. The analysis presented reveals that the direct torque control injects a negative sequence voltage and manipulates the torque angle to meet the control objectives when a fault occurs. The co-simulation of finite element analysis and a multi-physic circuit simulator is used to validate the response of the hysteresis-based controller to the machine health. The results indicate that the hysteresis comparators have the ability to mask the impact of the faults in the direct-torque-control-driven permanent magnet synchronous machines.

A Design and Implementation of a New Control Based on Petri Nets for Three Phase PWM-Rectifier

This article introduces a novel and effective diagram based on direct instantaneous power control (DPC) of a PWM-controlled rectifier connected to the grid without a switching table. An optimum control vector of the PWM rectifier's input voltage, which depends on the switching states determined by a Petri nets controller, is adopted. This approach limits the instantaneous detection errors of reactive and active powers, maintains the DC bus voltage at a reference level, and ensures current close to a sinusoidal wave, guaranteeing operation at a unit power factor. The instantaneous tracking errors of active and reactive powers and the angular position of the voltage are used as input variables for the proposed controller, which then selects the best control vector for the converter based on the transition of a Petri net. The significant advantages of DPC based on Petri nets compared to traditional switching tables are that hysteresis comparators are not required, and the classical regulation of active and reactive powers is achieved in all sectors. Simulation and testing findings demonstrated excellent performance, supporting the viability of the suggested control approach using Petri nets.

Stability analysis and speed control of brushless DC motor based on self-ameliorate soft switching control methods

In recent years, electric vehicles are the large-scale spread of the transportation field has led to the emergence of brushless direct current (DC) motors (BLDCM), which are mostly utilized in electrical vehicle systems. The speed control of a BLDCM is a subsystem, consisting of torque, flux hysteresis comparators, and appropriate switching logic of an inverter. Due to the sudden load torque variation and improper switching pulse, the speed of the BLDCM is not maintained properly. In recent research, the BLDC current control method gives a better way to control the speed of the motor. Also, the rotor position information should be the need for feedback control of the power electronic converters to varying the appropriate pulse width modulation (PWM) of the inverter. The proposed optimization work controls the switching device to manage the power supply BLDCM. In this proposed self-ameliorate soft switching (SASS) system is a simple and effective way for BLDC motor current control technology, a proposed control strategy is intended to stabilize the speed of the BLDCM at different load torque conditions. The proposed SASS system method is analyzing hall-based sensor values continuously. The suggested model is simulated using the MATLAB Simulink tool, and the results reveal that the maximum steady-state error value achieved is 4.2, as well as a speedy recovery of the BLDCM's speed.

A Self-Supplied Power Optimizer for Piezoelectric Energy Harvesters Operating under Non-Sinusoidal Vibrations

A self-supplied circuit that is able to significantly increase the power delivered to a bridge rectifier by a Resonant Piezoelectric Vibration Energy Harvester (RPVEH) is presented and discussed. The proposed circuit, called the Energy Harvester Power Optimizer (EHPO), is implemented by means of a switch-mode converter that emulates a negative capacitance. Unlike switch-mode impedance emulators, based on sophisticated tracking algorithms requiring lossy microcontrollers, EHPO exploits a very light control circuit based on a hysteresis comparator. The EHPO is self-supplied since it does not need an external supply, but it draws the energy for its operation directly from the RPVEH. Moreover, it is developed without the assumption of purely sinusoidal vibrations. Experimental results show that the EHPO can significantly increase the power delivered to a rectifier, both in the case of sinusoidal vibrations (percent gain of the net extracted power up to about 190%) and non-sinusoidal vibrations (percent gain of the net extracted power up to about 245%), regardless of the shape of the forcing acceleration and regardless of the RPVEH resonance frequency.

CONTROL OF DOUBLY FED INDUCTION GENERATOR USING ARTIFICIAL NEURAL NETWORK CONTROLLER

In this paper, we propose a direct power control (DPC) based on an artificial neural network (ANN-DPC) for the doubly-fed induction generator (DFIG), which is applied to the wind turbine system. The main objective of this intelligent technique is to replace the switching table and the hysteresis comparators with a neural control to reduce the ripple to the level of current and power. Field-oriented control (FOC) is traditionally achieved using a conventional proportional-integral controller (PI). The power ripples are reduced, and a reasonable total harmonic distortion rate is ensured by using an ANN-DPC.

A Virtual Vector Based DTC Scheme With Enhanced Resolution for Dual Inverter Fed Five-Phase IM Drives

A virtual voltage vector based direct torque control (DTC) scheme with enhanced resolution for five-phase induction motor (IM) drives with open-end stator windings, fed by two inverters, is proposed in this article. In the proposed scheme, the voltage space vector plane is divided into 20 sectors, by using 40 virtual voltage vectors produced as resultants of the virtual voltage vectors of the individual inverters thereby substantially increasing the sector resolution compared to the 10-sector based conventional five-phase DTC schemes. This DTC scheme incorporates a five-level hysteresis comparator for torque control and the required voltage vectors of different magnitudes are produced by appropriately combining the vectors of the two inverters. The increased sector resolution along with five-level hysteresis torque controller facilitates finer flux and torque control. As the effective common mode voltage in the motor windings is made zero in every switching period, both inverters can be connected to a common dc supply without causing circulation of zero sequence current. The proposed scheme is validated by performing experiment on a five-phase IM drive.

DTC-SVM οf Sensorless Five-phase Induction Machine Using Extended Kalman Filter

This work relates to the study of direct torque control based on space vector modulation applied on five-phase induction machine. It is well established that the conventional direct torque control using hysteresis comparators suffers from high torque ripples and variable switching frequency. The most common solution to those problems is the use of space vector modulation. In the other hand, this paper aims also to design an extended Kalman filter observer for speed/flux estimation, which improves not only the control performances by using a sensorless algorithm but also can lower the cost and increase the reliability of the system. Both theoretical principle and simulation results of the sensorless control method of multiphase drive will be conducted to verify the effectiveness of the proposed control approach.

A 1-W, 6.78-MHz Wireless Power Transfer System With Up-to-16.1% Light-Load Efficiency Improvement and Instant Response Through Single-Cycle-Based D TX Control

This article presents a 6.78-MHz wireless power transfer system with transmission power control. The proposed receiver (RX) with a simplified 0X/1X structure can achieve single-stage regulation in series–series resonant tank, where the charge and discharge cycle are only dependent on the hysteresis comparator. Asymmetric pulsewidth modulation is adopted in the proposed transmitter (TX), where the duty ratio ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${D}_{\text{TX}}$</tex-math></inline-formula> ) is switched based on the charge or discharge cycle of RX. With the proposed single-cycle-based <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${D}_{\text{TX}}$</tex-math></inline-formula> control, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${D}_{\text{TX}}$</tex-math></inline-formula> will be switched to 0.25 in the discharge cycle, while it is 0.5 in the charge cycle for maximum power transmission. Therefore, the end-to-end (E2E) efficiency especially at light-load conditions can be improved, and the recovery time is nearly instant when loading changes suddenly, i.e., neglectable voltage droop can be achieved. The RX is implemented by a printed circuit board and the TX is fabricated in a 0.18- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m CMOS technology. In the measurement, an output power range from 10 to 1000 mW is achieved with 60.6% peak E2E efficiency. The significant E2E efficiency improvement is observed over 10–255 mW and the maximum improvement is 16.1%. The measured load transient response verifies that the proposed design has instant response and neglectable voltage droop.

Fast and Low-Power CMOS and CNFET based Hysteresis Voltage Comparator

This paper presents CMOS and CNFET based hysteresis voltage comparators for low-voltage applications. The proposed CMOS and CNFET hysteresis comparators require merely 1.6 and 0.26 µW of power, respectively, which is less than one tenth of the power dissipated by the other advanced hysteresis comparators designs available in literature. The propagation delay observed in the proposed CMOS and CNFET hysteresis comparators are 162 and 47 ps, respectively, which is almost half the delay exhibited by the other hysteresis comparators. Overall, a 93–99% reduction in Power Delay Product (PDP) can be achieved. Furthermore, the proposed design requires only nine transistors compared to the 11–17 transistor requirement in conventional hysteresis comparators, thus saving up to 47% of chip area.

A 12.8-Gb/s 0.5-pJ/b Encoding-Less Inductive Coupling Interface Achieving 111-GB/s/W 3D-Stacked SRAM in 7-nm FinFET

A 12.8-Gb/s 0.5-pJ/b inductive coupling inter-chip wireless communication interface for a 3D-stacked SRAM has been developed in a 7-nm FinFET process. A new clocked hysteresis comparator that eliminates encoding for synchronous communication achieves 1.49 times higher data rate and 36% lower energy consumption compared to conventional synchronous communication using Manchester encoding. Inter-chip communication at 0.5-pJ/b 12.8-Gb/s was confirmed using test chips. The proposed interface for a 4-hi 3D-stacked SRAM module achieves a 1.7-TB/s/mm2 IO area efficiency and 111-GB/s/W bandwidth per power, representing a two-orders-of-magnitude improvement in area efficiency over a state-of-the-art interface for a 3D-stacked SRAM with competitive per-power bandwidth.