Control Of Induction Machine Research Articles

Multi-phase weighted stator current tracking using a hyper-plane partition of the control set

This paper presents a new optimization technique for Finite Control Set Model Predictive Control (FCS-MPC) of multi-phase induction machines. The proposal allows for a fast computation of the control signal while simultaneously considering stator currents in the α−β (torque producing) plane and the x−y (harmonics) plane. The combinatorial search of the optimization phase is eliminated. Also, unlike previous approaches, the proposed region identification algorithm can be utilized in conjunction with weighting factors in the cost function. The optimization is done using a hyper-plane partition of the control set. The partition provides the weighted FCS-MPC solution with significantly less computation needs allowing for shorter sampling periods. The method is tested experimentally in a 5-phase induction motor showing enhanced results.

التحكم في سرعة المحركات الحثية باستخدام التحكم العددي ذو الحلقة المغلقة

In this study, the scalar control approach is applied to the control of induction motors three phase. The approach of scalar control is based on the maintaining a constant ratio between voltage-to-frequency (V/f) ratio, both theoretical and simulation-based analyses were performed to examine the performance of the method, which was seen to be successfully applied in speed control for induction machine, making it suitable for various industrial application. Simulations are performed to change the speed by changing the input voltage and changing the input voltage frequency. Finally, the performance of the V/f controlled three-phase induction motor is investigated. Simulations are performed using different speed references and the results are presented.The results show that the V/f controlled three-phase induction motor has good speed tracking performance. The simulations are performed in MATLAB/SIMULING environment. Keywords: Induction motor, speed control, scalar control, closed loop, (V/f) control

Sensorless DTC Based on Artificial Neural Network for Independent Control of Dual 5-Phase Induction Machine Fed by a Three-Level NPC Inverter

Sensorless DTC Based on Artificial Neural Network for Independent Control of Dual 5-Phase Induction Machine Fed by a Three-Level NPC Inverter

Prof. Wei Xu Presents a Distinguished Lecture on Advances in Design and Control for Linear Induction Machines and Drive Systems [Society News

Prof. Wei Xu Presents a Distinguished Lecture on Advances in Design and Control for Linear Induction Machines and Drive Systems [Society News

Enhanced Cascade Sliding Mode Direct Thrust Control for Linear Induction Machine Based on Linear Metro

Enhanced Cascade Sliding Mode Direct Thrust Control for Linear Induction Machine Based on Linear Metro

Vector Control of Brushless Doubly-Fed Induction Machines Based on Highly Efficient Nonlinear Controllers

Vector Control of Brushless Doubly-Fed Induction Machines Based on Highly Efficient Nonlinear Controllers

Generalized Harmonic Injection Strategy for Multiphase Induction Machine Control

Generalized Harmonic Injection Strategy for Multiphase Induction Machine Control

Tensor Product Alternatives for Nonlinear Field-Oriented Control of Induction Machines

The paper presents a nonlinear field-oriented control technique based on the tensor product representation of the nonlinear induction machine model and the solvability of linear matrix inequalities. The nonlinear model has 32 quasi linear parameter-varying equivalent variants, and it is shown that only half of the models result in feasible controller. Two control goals are realized: torque control and speed control. The controller is a nonlinear state feedback controller completed by integral action. A new block diagram is investigated for speed control. The controller gains are designed by the solution of linear matrix inequalities to solve the Lyapunov inequality to obtain a stable and fast response and constraints on the control signal. The presented methods are verified and compared by simulations.

Design of Complex Vector Controller for High-Power Induction Machine Drive

In high-power drives of large commercial vehicles, the switching frequency of the inverter is always strictly limited to avoid high switching losses. In this paper, a high-performance complex vector controller in discrete domain is proposed to reduce the cross-coupling effect and improve control performance under low switching frequency. The discretization error of the induction motor model under different coordinate systems is explored, and a high-precision discrete induction motor model is proposed for the design of the complex vector controller and flux observer. In order to improve the dynamic response of the rotor flux linkage, the designed controller takes the current as the inner loop and the rotor flux linkage as the outer loop. Besides, the signal reconstruction strategy is proposed to solve the contradiction between the variable-step characteristics caused by synchronous modulation and the discretization process based on constant step size. Finally, the designed control strategy and analysis of the system are validly verified by simulation and experimental results.

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

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

Internet of Things-Based Control of Induction Machines: Specifics of Electric Drives and Wind Energy Conversion Systems

The Internet of Things (IoT) is introduced in systems with electrical machines, such as in electric drive systems, wind energy generating systems, and small and special machines, to remote monitor and control the operation for data acquisition and analysis. These systems can integrate with the equipment and retrofit the existing installations. At the end of the control loops there are always motors, or actuators, of big or small ratings, of rotating or linear movements, electrical or nonelectrical, which must produce the motion. This article analyses selected aspects of research and applications of IoT-based control in electric drive systems and of wind energy conversion systems with induction machines. Various applications and study cases of control systems of electrical machines with IoT technology are described. With the IoT-based control of induction machine systems operators can remotely monitor parameters and obtain accurate real-time feedback during fast changing duty cycle operation. Thus, IoT creates multipurpose instruments in the remote control of induction machines. The paper offers a comprehensive analysis of IoT-based control applications in the field of induction machines, with technical details of design, construction, experimental testing, and prototyping, that are useful to energy engineering specialists in the sector of electric drives and wind energy conversion systems.

Hybrid Flatness-Based Control of Dual Star Induction Machine Drive System for More Electrical Aircraft

Abstract This paper develops a precise method control system for tracking control of a power drive system based on a multi-phase machine under motor parameter and load torque variations. By adding a simple feedforward term based on the flatness theory, a conventional flux oriented control (FOC) can be enforced to have a perfect tracking performance under model parameter and load torque variations. Hence, a hybrid flatness-based control (HFBC) technique is applied to the control of a dual star induction machine (DSIM) and compared to a classical vector control strategy regarding tracking behaviour, robustness, and perturbations rejection. Finally, the simulation and experimental results are provided to verify the effectiveness of the proposed HFBC under uncertainties such as motor parameter and load torque variations. Furthermore, an enhancement of the drive system’s control performances is demonstrated by the improvement of the technique of separation of the objectives of tracking and disturbance rejection. The simulation and experimental results are presented, demonstrating the superiority of the HFBC.

Fault Tolerant Control of a Dual Star Induction Machine Drive System using Hybrid Fractional Controller

Abstract This paper presents a novel fault tolerant control (FTC) strategy for a dual star induction machine (DSIM) based on the combination of two types of robust controllers, namely a proportional resonant (PR) controller for current regulation and a fractional order PI (FOPI) for speed regulation. This FTC is associated with an indirect rotor indirect rotor field-oriented control (IRFOC) strategy. Fault feedforward compensation of the current components is introduced using the residual signal generated by the calculations passing through the PR controller. The fractional-order PI controller is applied as a feedforward fractional-order perturbation observer to the speed control loop, which attempts to minimise the error induced by the fault. In this context, a fault-tolerant control scheme is achieved. The performance characteristics of the proposed fault tolerant control for a dual star induction machine drive are compared with the fault tolerant control based on the conventional integer order IP (IOPI) to verify the effectiveness of the proposed FTC scheme under various conditions, by examining the robustness of the control in the presence of faults. To evaluate the performance of the proposed technique, simulation results are obtained using the Matlab/Simulink environment. According to the obtained simulation results, the proposed FTC system achieves significantly better responses than the conventional IRFOC system in terms of harmonics in the stator currents, and low oscillations in the electromagnetic torque response.

Speed Sensorless Model Predictive Current Control of Linear Induction ‎Machines in Urban Transit

Speed Sensorless Model Predictive Current Control of Linear Induction ‎Machines in Urban Transit

A Single DC Source Multilevel Inverter with Extended Linear Modulation Range to the Full Base Speed and Predictive Capacitor Control for Induction Machine Drives

A Single DC Source Multilevel Inverter with Extended Linear Modulation Range to the Full Base Speed and Predictive Capacitor Control for Induction Machine Drives

Nonlinear Efficiency-Optimal Model Predictive Torque Control of Induction Machines

Nonlinear Efficiency-Optimal Model Predictive Torque Control of Induction Machines

Contribution to the Improvement of Sensorless DTC-SVM for Three-Level NPC Inverter-fed Induction Motor Drive

This paper deals with the high performance of multi-level direct torque control (DTC) for induction machines without speed and stator flux sensors. The estimation is performed using a sliding mode observer, which is known for its robustness in high and low-speed operations, the control is based on a backstopping speed controller. This control technique was introduced years ago to circumvent the problems of sensitivity to parametric variations, it presents a high dynamic but their major problems are the variable switching frequency, the size and complexity of the switching tables, and undulations of the torque. The proposed approach is to replace switching tables with constant switching frequency control using three-level spatial vector modulation (SVM). Theoretical elements and simulation results are presented and discussed. As a result, the flux and torque ripple of three-level DTC-SVM control is greatly reduced compared to the flux and torque ripple of DTC-classic control. The advantages of the training system have been validated by the simulation results.

Sensorless Saliency-Based Control of Dual Induction Machines Under Dynamic Load Imbalances Using Three Current Sensors

To perform vector control of single-inverter dual induction motors, drives are standardly equipped with current and position sensors. In medium-power railway applications, a shaft encoder is usually mounted on each motor, and the inverter output current is measured using two current sensors. Yet, this configuration features some disadvantages. First, torque-sharing cannot be computed because stator current of each motor is unknown. Similarly, saliency extraction of each motor is not achievable since individual current drawn by each motor is not measured. An option that achieves torque-sharing calculation is to attach two current sensors to each motor, provided that both rotor positions are known. However, industrial inverter/control platforms considered offer a maximum of three input channels for current sensors. Besides, some industry fields tend towards encoderless speed control. Therefore, this paper proposes to use three current sensors in total and no shaft encoders. Thanks to a special current sensor arrangement and a voltage step excitation method, saliency-based encoderless control is achieved. In addition, a method is presented to estimate torque-sharing. Experimental measurements, taken on a dual induction motor test bench, will show the capability of the proposed methodology to identify individual loading as well as excellent encoderless control performance.

Current boundary-based predictive current control of induction machines with lower switching frequencies

Current boundary-based predictive current control of induction machines with lower switching frequencies

Single-Stage Standalone Photovoltaic Water Pumping System Using Predictive Torque Control (PTC) of Induction Machine

Solar energy is widely utilized for water pumping systems, particularly in remote areas. However, such systems have different configurations and strategies, each with its own advantages and drawbacks. To design a suitable system, this paper proposes a method that utilizes a single-stage conversion system with hydraulic storage. In this method, the predictive torque controller (PTC) adjusts the inverter switching while the electrical storage in batteries is replaced by the potential energy of water in tanks. The PTC works side-by-side with a maximum power point tracking (MPPT) technique to supply the optimal power to the water-pumping Induction Motor (IM). This maximum power tracking is maintained during the day hours to provide and store water, whereas the water supply is guaranteed due to the gravity at night. The effectiveness of the proposed system is evaluated through MATLAB/Simulink-based results, demonstrating that the single-stage configuration outperforms the double-stage configuration in terms of power optimization, torque ripples, and power loss reduction. Furthermore, the suggested system offers the advantage of cost-effective installation due to its simple structure.