Double Star Induction Motor Research Articles

Modified load angle direct torque control for dual star motor using fuzzy logic

Space Vector Modulation (SVM) has emerged as a prominent alternative for motor control, particularly within the framework of Direct Torque Control (DTC-SVM). SVM leverages variations in the load angle, which result from changes in motor torque, to generate the appropriate voltage vectors. The conventional approach to this method involves a single Proportional-Integral (PI) regulator, which is characterized by a constant switching frequency and the capability to reduce ripples in torque, flux, and current. Despite these advantages, the PI regulator may face challenges in maintaining optimal performance under varying load conditions. This study seeks to enhance the performance of the DTC-SVM strategy by integrating Fuzzy Logic into the PI regulator. The primary objective is to improve the accuracy and responsiveness of the load angle control, thereby optimizing the motor's operational efficiency. The proposed SVM-Fuzzy control scheme is designed to address the limitations of the traditional PI regulator, offering a more adaptive and robust solution for motor control. To evaluate the effectiveness of the proposed approach, extensive simulations were conducted using Matlab Simulink. The SVM-Fuzzy strategy was compared against the conventional SVM-PI approach to assess its performance in terms of torque, flux, and current regulation. The SVM-Fuzzy control scheme significantly enhances efficiency, stability, and load angle precision, particularly in Double Star Induction Motors (DSIM). It also ensures the durability and reliability of the motor control system under different operating conditions.

DTC-SVM strategy of double star induction motor using sliding mode controller enhanced by fuzzy logic

Extensive research and numerous articles on Direct Torque Control (DTC) systems have consistently highlighted various deficiencies associated with the employment of hysteresis control units. Specifically, these issues include significant torque and stator flux ripples, as well as distortions in stator current. Additionally, the sensitivity to parametric variations stemming from Proportional-Integral (PI) controllers poses a challenge due to the complexities involved in their adjustment. To address these drawbacks, this article explores the implementation of Space Vector Modulation DTC (SVM-DTC) technology integrated with a Sliding Mode Controller (SMC). The proposed control scheme for DTC amalgamates the benefits derived from SMC control and the SVM algorithm. The SMC controller is utilized to oversee PI controllers, employing this nonlinear technique ensures superior dynamic performance and robust resistance against external disturbances. Notwithstanding its advantages, one notable issue with SMC is chattering. To mitigate this phenomenon, we adopt an approach that integrates Fuzzy Logic with SMC. By replacing the saturation function (Sat) with a fuzzy inference system, we effectively minimize chattering. The simulation is conducted using MATLAB SIMULINK. Comparative analysis between DTC-SVM strategy and traditional methods including standard SMC and Fuzzy-enhanced Sliding Mode Controller (FSMC), demonstrates that our hybrid nonlinear controller exhibits high efficiency and remarkable robustness.

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

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

Model reference adaptive backstepping control of double star induction machine with extended Kalman sensorless control

Introduction. Newly, the design of a controller for speed control of double star induction motor as a research focus. Consequently, backstepping technique is used to recursively construct a stable control law for speed and flux. Nevertheless, this control law coming from backstepping requires the knowledge of speed and flux values; in practice the measurement sensors are expensive and fragile. The novelty of this work consists to propose a control strategy which based on accurate Kalman filter observer that estimates speed, flux and torque. This extended Kalman filter is an optimal state estimator and is usually applied to a dynamic system that involves a random noise environment. Purpose. Apply a backstepping control of double star induction motor based on principle of rotor flux orientation. This approach consists in finding a Lyapunov function that allows deducing a control law and a modified adaptation rule is referred and sufficient conditions for the stability of the command-observer, in contrast to other techniques who use nonlinear principle. Results. The simulation results are shown to illustrate the performance of the proposed scheme under parametric uncertainties by simulation on MATLAB. The obtained results showed the robustness of the sensorless control in front of load and parameters variation of double stator induction motor. The research directions of the model were determined for the subsequent implementation of results with simulation samples.

Robust Flux and Speed State Observer Design for Sensorless Control of a Double Star Induction Motor

In this paper, a robust flux and speed observer for sensorless control of a double star induction motor is presented. Proper operation of vector control of the double star induction motor requires reliable information from the process to be controlled. This information can come from mechanical sensors (rotational speed, angular position). Furthermore, mechanical flux and speed sensors are generally expensive and fragile and affect the reliability of the system. However, the control without sensors must-have performance that does not deviate too much from that which we would have had with a mechanical sensor. In this framework, this work mainly deals with the estimation of the flux and speed using a robust state observer in view of sensorless vector control of the double star induction motor. The evaluation criteria are the static and dynamic performances of the system as well as the errors between the reference values and those estimated. Extensive simulation results and robustness tests are presented to evaluate the performance of the proposed sensorless control scheme. Furthermore, under the same test conditions, a detailed comparison between the proposed state observer and the sliding mode-MRAS technique is carried out where the results of its evaluation are investigated in terms of their speed and flux tracking capability during load and speed transients and also with parameter variation. It is worth mentioning that the proposed state observer can obtain both high current quality and low torque ripples, which show better performance than that in the MRAS system.

Design of a New Direct Torque Control Using Synergetic Theory for Double Star Induction Motor

This paper describes a new Direct Torque Control (DTC) scheme to the synthesis of controllers based on the theory of synergetic control (SC) for two level inverter fed double star induction motor (DSIM) drive. The controllers’ synthesis method is totally analytical, and is based on non-linear models of the DSIM. The proposed synergetic control scheme requires creation of the space attractors and artificial manifolds that reflect the desirable operating modes of the DSIM. The combination between the DTC and the SC laws provides asymptotic stability with respect to the required operating regimes, reduces the THD of stator currents, invariance to external disturbances, and robustness to variation of DSIM parameters. The performance of the proposed approach has been tested under different operating conditions. With respect to their dynamic characteristics, synergetic controllers (SCs) are superior to the existing types of PI, Sliding Mode (SM) and Fuzzy Logic (FL) controllers.

Study of Dual Stator Induction Motor in Photovoltaic-Fuel Cell Hybrid Pumping Application

This paper discusses the modeling of hybrid Photovoltaic/Fuel cell pumping. This system comprises a photovoltaic generator and a fuel cell, two DC/DC converters, two of inverters which supply a double star induction motor (DSIM) which drives the shaft of a centrifugal pump. The evaluation of the water requirements, the total dynamic head (TDH) and the flow are of great importance to evaluate the various powers allowing the determination of the size of the pumping system. The global proposed system is sized and simulated under Matlab/Simulink Package. The obtained results under different metrological conditions show the effectiveness of the proposed hybrid pumping system.

Novel design of an optimized synergetic control for dual stator induction motor

PurposeThis paper aims to present a contribution to improve the performance of vector control scheme of double star induction motor drive (DSIM) by using an optimized synergetic control approach. The main advantage of synergetic control is that it supports all parametric and nonparametric uncertainties, which is not the case in several control strategies.Design/methodology/approachThe suggested controller is developed based on the synergistic control theory and the particle swarm optimization (PSO) algorithm which allow to obtain the optimal parameter of suggested controller to improve the performance of control system.FindingsTo show the benefits of proposed controller, a comparative simulation results between conventional PI controller, sliding mode controller and suggested controller were carried out.Originality/valueThe obtained simulation results illustrate clearly that synergetic controller ensures a rapid response, asymptotic stability of the closed-loop system in the all range operating condition and system robustness in presence of parameter variation in all range of operating conditions.

Direct space vector modulation for matrix converter fed dual star induction machine and neuro-fuzzy speed controller

This paper presents the modeling, design, and simulation of an adaptive neuro fuzzy inference strategy (ANFIS) for controlling the speed of the Double Star induction Machine (DSIM), the machine is fed by three phase direct matrix converter which makes directly AC-AC power conversion is modeled using Direct Space Vector Modulation technique(DSVM) for direct matrix converter. Double star Induction motor is characterized by highly non-linear, complex and time-varying dynamics and inaccessibility of some of the states and outputs for measurements. Hence it can be considered as a challenging engineering problem in the industrial sector. Various advanced control techniques has been devised by various researchers across the world. Some of them are based on the neuro-fuzzy techniques. The main advantage of designing the ANFIS coordination scheme is to control the speed of the DSIM to increase the dynamic performance, to provide good stabilization. To show the effectiveness of our scheme, the proposed method was simulated on an electrical system composed of a 4.5 kW six-phase induction machine and its power inverter. Digital simulation results demonstrate that the deigned ANFIS speed controller realize a good dynamic of the DSIM, a perfect speed tracking with no overshoot, give better performance and high robustness.

Sliding Mode Control Based on Backstepping Approach for a Double Star Induction Motor (DSIM)

Sliding Mode Control Based on Backstepping Approach for a Double Star Induction Motor (DSIM)

Modeling and digital field-oriented control for double star induction motor drive

Modeling and digital field-oriented control for double star induction motor drive

Optimal vector control to a double-star induction motor

The problem of energy optimization of a Double Star Induction Motor (DSIM) using the concept of a Rotor Field Oriented Control (RFOC) can be treated by an Optimal Control Strategy (OCS). Using OCS, a cost-to-go function can be minimized and subjected to the motor dynamic equations and boundary constraints in order to find rotor flux optimal trajectories. This cost-to-go function consists of a linear combination of magnetic power, copper loss, and mechanical power. The Dynamic equations are represented by using a reduced Blondel Park model of induction motor. From the Euler-Lagrange equation, a system of nonlinear differential equations is obtained, and analytical solutions of these equations are achieved so as to obtain a time-varying expression of a minimum-energy rotor flux. The current study discusses a saturation model with respect to the rotor flux, which has significant influence in the motor's parameters. A comparative study of simulation results given from conventional and optimized RFOC proves the presented strategy's validity and effectiveness.

Fuzzy logic field oriented control of double star induction motor drive

An indirect field oriented control of a double star induction motor drive with a conventional PI and fuzzy logic controller based on four rules is presented in this paper. To realize a control of this motor, a DC supply and a PWM voltage source inverter (VSI) are introduced. Performance of the proposed control schemes under load disturbances and parameter variations is studied through simulations. The simulation results regarding the speed response with both controllers are presented and discussed.

Fuzzy logic based speed control of indirect field oriented controlled Double Star Induction Motors connected in parallel to a single six-phase inverter supply

Speed control of two Double Star Induction Motors operating in parallel configuration with Indirect Field Oriented Control using a Fuzzy Logic Controller is investigated. The two motors are connected in parallel at the output of a single six-phase PWM based inverter fed from a DC source. Performance of the proposed method under load disturbances is studied through simulations. A comparison of the speed response with the two controllers is presented and analyzed.

Analytical solution of optimized energy consumption of Double Star Induction Motor operating in transient regime using a Hamilton–Jacobi–Bellman equation

The problem of energy optimization of a DSIM (Double Stator Induction Motor) using the concept of a RFOC (Rotor Field Oriented Control) can be treated by an OCS (Optimal Control Strategy). Using OCS, a cost-to-go function can be minimized and subjected to the motor dynamic equations and boundary constraints in order to find rotor flux optimal trajectories. This cost-to go function consists of a linear combination of magnetic power, copper loss, and mechanical power. The dynamic equations are represented by using a reduced Blondel Park model of the DSIM. From the HJB (Hamilton–Jacobi–Bellman) equation, a system of nonlinear differential equations is obtained, and analytical solutions of these equations are achieved so as to obtain a time-varying expression of a minimum-energy rotor flux. This analytical solution of rotor flux achieved maximum DSIM's efficiency and was implemented in the ORFOC (optimal rotor flux oriented control) and compared to the conventional RFOC at different dynamic regime of the DSIM. Simulation results are given and improved the effectiveness of the proposed strategy.

A Neural Network Based Speed Control of a Dual Star Induction Motor

This paper propose the use of artificial neural networks to control the speed of a Double Star Induction Motor drives fed by a two matrix converter using Venturini modulation algorithm, The advent of the field oriented with modern speed control technique has partially solved DSIM control problems because it is sensitive to drive parameter variations and performance may deteriorate if conventional controllers are used. Neural network based controller is considered as potential candidates for such an application. In this work the simulations results are provided to evaluate performance of the proposed control strategy. DOI: http://dx.doi.org/10.11591/ijece.v4i6.6343

Speed Control of Doubly Star Induction Motor Using Direct Torque DTC Based to on Model Reference Adaptive Control (MRAC)

This paper presents the analysis and simulation of the control of double star induction motor, using direct torque control (DTC) based on model reference adaptive control algorithm (MRAC). The DTC is an excellent solution for general- purpose induction drives in very wide range the short sampling time required by the TC schemes makes them suited to a very fast torque and flux controlled drives as well the simplicity of the control algorithm. DTC is inherently a motion sensorless control method. The model reference regulator (MRAC) can improve the double star induction motor performance in terms of overshoot, rapidity, cancellation of disturbance, and capacity to maintain a high level of performance. Simulation results indicate that the proposed regulator has better performance responses. The implementation of the DTC applied to a double star induction motor based on model reference regulator is validated with simulated results.

Modelling and simulation of a double‐star induction machine vector control using copper‐losses minimization and parameters estimation

AbstractThis paper shows that it is possible to extend the principle of field‐oriented control (FOC) approach to a double‐star induction motor (DSIM). In the first stage, a robust variable structure current controller based on space phasor voltages PWM scheme is established. In this current controller design, only the stator currents and rotor speed sensors are used. In the second stage, the FOC method developed for DSIM is motivated by the minimization of the copper losses. The developed approach uses a loss model controller (LMC) and an adaptive rotor flux observer to compute the adequate rotor flux value minimizing the copper losses. The control variables are the stator currents or the machine input power. Compared to the constant rotor flux approach, it is proved that higher performances are achieved. However, the sensitivity of the FOC to parameter error of the machine still remains a problem. To guarantee the performance of the vector control, the stator and rotor resistances are adapted on‐line, based on the Lyapunov theory. An appropriate choice of the reference model allows building a Lyapunov function by means of which the updating law can be found. The simulation results show the satisfactory behaviour of the proposed identification algorithm. Copyright © 2002 John Wiley & Sons, Ltd.