Controlled Induction Motor Research Articles

Design of Novel STASOSM Controller for FOC Control of Dual Star Induction Motor Drives

In this paper, a Novel Super-Twisting Algorithm combined with Improved Second - Order Sliding Mode (NSTASOSM) for the Field-Oriented Control (FOC) of high performance SPIM drives is proposed. This structure, on the one hand, effectively solves the weaknesses of traditional backstepping control (BS) and sliding mode (SM) control that are the dependent on the change of parameters, load disturbance and the phenomenon of chattering, on the other hand, increases the convergence speed and the reference tracking ability, enhance the robust and stably of drive systems even when working in conditions of uncertain parameter and load disturbances, eliminates the chattering phenomenon. The obtained results by simulation using the Matlab/ Simulink tool verified the performance of this proposed control structure.

Current Sensor Fault-Tolerant Control Strategy for Speed-Sensorless Control of Induction Motors Based on Sequential Probability Ratio Test

In the speed-sensorless vector control of induction motors (IMs), the speed estimation accuracy suffers from the deteriorated current measurement caused by the current sensor faults, such as open circuit in one phase, DC bias, and odd harmonics. In this paper, a novel speed estimation strategy based on the current sensor fault-tolerant control is proposed to improve the speed estimation accuracy under the current sensor faults. First, to detect the current sensor faults in real time, the sequential probability ratio test is introduced to the system by using the innovations of the extended Kalman filter (EKF). Second, to ensure speed estimation accuracy, a double-cascading second-order generalized integrator (DSOGI) is employed to reconstruct the faulty current information when a fault is identified. Finally, the reconstructed current information is fed back to the sequential probability extended Kalman filter (SPEKF), which estimates the rotor speed of the IM, and high-accuracy speed estimation under the condition of current sensor faults is achieved. The effectiveness of the proposed strategy is validated by a series of experiments, which were conducted on a 3 kW induction motor drive platform.

Current sensor fault-tolerant control based on modified Luenberger observers for safetycritical vector-controlled induction motor drives

Vector controlled drives require stator current information for use in current feedback and/or state variable estimators. That is why the detection and compensation of possible CS damage is so important. This article focuses on current sensor (CS) fault-tolerant control (FTC) in induction motor (IM) drive systems. In contrast to solutions known from the literature, two Modified Luenberger Observers (MLO) were applied, allowing for high-quality estimation of currents used in the detector and fault compensator. In a simple implementation of a detection algorithm based on residuals, an adaptive threshold coefficient was employed, enabling effective detection of various types of faults, regardless of whether the second current sensor was faulty or intact. The presented solution was evaluated during both motor and regenerative operation, with faults occurring in transient states, unlike solutions known in the literature.

Design Of Maximum Torque Per Ampere Control Method In Squirrel Cage Three-Phase Induction Motor

Improving the performance of three-phase induction motors is currently carried out by various control methods. One of them is controlling a three-phase induction motor using the Maximum Torque Per Ampere (MTPA) method. This paper focuses on the study of modeling specific motor models using the MTPA method. The purpose of the study is to prove that with the squirrel cage motor model, the speed can be increased above its rating. The MTPA method is a method of controlling a three-phase induction motor by controlling the current from the torque speed. Modeling is tested to see the responsiveness of the modeled system. The experimental results were tested using two-speed references and the system showed that MTPA control induction motors can improve the performance of three-phase induction motors. The results from the design show that the MTPA method can increase the performance of three-phase induction motors to reach 84.4%. The results of this study can be used as one way to model induction motors.

Sliding-Mode Control of Linear Induction Motor Based on Exponential Reaching Law

As a strongly coupled, multivariable, high-order nonlinear, time-varying complex system, a linear induction motor is susceptible to outside disturbances and mismatched parameters. Because of its straightforward control mechanism and fixed PI value, the traditional PI regulator is frequently utilized in linear induction motor speed control systems. However, because of these limitations, it frequently falls short of meeting the high-performance control needs of the motor in complex operating conditions. In order to solve the contradiction between the sliding-mode motion reaching time and vibration, the sliding-mode variable structure control is applied to the linear induction motor speed control system in this paper. The sliding-mode controller is designed using the exponential reaching law method, and the designed system is analyzed through simulation. The findings demonstrate how the controller enhances the system’s robustness and disturbance resistance by bringing about the advantages of rapidity, stability, no overshooting, and a strong resistance to load disturbance.

Research on Parameter Identification of Induction Motor Based on Model Reference Adaptive System

Abstract This paper proposes a novel online parameter identification method based on model-reference adaptive systems to achieve more precise control of induction motors. This method efficiently and accurately obtains the parameters of induction motors during operation, facilitating effective control. Experimental validation is conducted on a hardware-in-the-loop test platform, demonstrating that the proposed online parameter identification method for induction motors achieves accurate parameter estimation with the advantages of high identification speed and precision. Control experiments on induction motors using the identified parameters further validate the feasibility of the proposed method for online parameter identification.

A non-isolated PFC bridgeless SEPIC-Cuk converter with adaptive PI controller for induction motor

In general, the induction motor (IM) is extremely nonlinear in nature and frequency dependent. In most cases, the power generated by the IM has a low power factor (PF), which exhibits detrimental effect on the extent to which the whole transmission and distribution system functions. Since there exists more current harmonics as an outcome of minimized PF, the efficiency of the power system suffers due to transmission line heating and voltage distortion characteristics. Therefore, this paper proposes a power factor correction (PFC) method to overcome the aforementioned issues. Here, by the utilization of AC-DC bridgeless SEPIC-Cuk converter, the power quality is improved by reducing reactive power consumption and enabling better control of voltage and current outputs. To maintain the stable DC link voltage with reduced ripples, the adaptive proportional-integral (PI) controller is used in this work. The three-phase voltage source inverter (VSI) transitioning function is controlled by cascaded fuzzy logic (CFL) controller, which is also utilized for regulating the speed of the three-phase IM. Implementing the proposed control strategy improves power quality significantly by reducing total harmonic distortion (THD). The proposed system is simulated in the MATLAB platform and the attained outcomes, it is clear that the proposed system is highly effective.

Fault-Tolerant Control Based on Current Space Vectors against Total Sensor Failures.

This paper proposes a fault-tolerant control (FTC) strategy using the current space vectors to diagnose sensor failures and enhance the sustained operation of a field-oriented (FO) controlled induction motor drive (IMD). Three space vectors are established for the sensor fault diagnosis technique, including one converted from the measured currents and the other two calculated from the current estimation technique, respectively, measured and with reference speeds. A mixed mathematical model using three space vectors and their components is proposed to accurately determine the fault condition of each sensor in the motor drive. After determining the operating status of each sensor, if the sensor signal is in good condition, the feedback signal to the controller will be the measured signal; otherwise, the estimated signal will be used instead of the failed signal. Failure states of the various sensors were simulated to check the effectiveness of the proposed technique in the Matlab/Simulink environment. The simulation results are positive: the IMD system applying the proposed FTC technique accurately detected the failed sensor and maintained stability during the operation.

Open-phase fault-tolerant control of encoderless Y-connected 3-phase induction motors

Open-phase fault-tolerant control of encoderless Y-connected 3-phase induction motors

Sensorless speed controller of an induction motor with MRAS-based model predictive control

Speed sensors play critical role in induction motor (IM) control systems. However, the use of these sensors cause several drawbacks such as increasing the overall cost, decreased reliability on control and increased noise problems in data acquisition. The sensorless control methods also have been proposed in control systems of IM to increase the overall performance. On the other hand, model predictive controllers (MPCs) which is one of the most recently used controller methods require the speed measurement to perform speed and torque control of an IM. In addition to control method, the topology of voltage source inverter (VSI) affects the overall efficiency of the IM drive because of its losses and total harmonic distortion (THD) ratios delivered by the topology. The main proposal of this study is to implement an IM drive built with a three-level active neutral point clamped (3L-ANPC) voltage source inverter (VSI) and to propose an MPC that eliminates sensor requirement in speed control of IM. The proposed IM drive takes benefits of multilevel inverter topology, which reduces the torque ripple, enables low switching frequency and provides decreased harmonic distortion. The switching pulses of ANPC VSI are generated by the proposed sensorless MPC method for controlling the torque of IM. The modelling and experimental verification of the ANPC based IM drive have been carried out and the sensorless MPC controller has been validated in this study. There two types of model reference adaptive system (MRAS) have been proposed to ensure precise estimation of IM speed that should be supplied to MPC controller. These MRAS methods are titled as the rotor flux based model reference adaptive system (MRASF), and the stator current based model reference adaptive system (MRASCC) according to estimation references. The proposed MPC-based IM drive has been analyzed under variable speed and torque circumstances to detect the efficiency and reliability of MRASF and MRASCC algorithms. The efficiency indicators such as flux and torque responses, and speed control of the suggested MPC IM drive are validated with experimental analysis. The results of revealed that the IM effectively tracks the reference speed and produces the required torque depending to the precise control of proposed MPC algorithm.

Control and Performance Analysis of an Indirect Matrix Converter Fed Triple Star Induction Motor

Efficient operation is a recommended factor in most of industrial applications. In this paper, an indirect matrix converter (IMC) topology is developed and proposed to substitute the classical (AC/DC/AC) three phase converter topologies; where the control strategy is frequently performed with a voltage source inverter (VSI). Large electrolytic capacitors are viewed as hazardous due to their short lifetime compared to ordinary capacitors and power switches, as well as their contribution to the total bulk and weight of the converter. Matrix converters may be the answer to getting rid of the capacitor, shrinking the converter, and improving its efficiency (MC). These advantages are offset by the fact that the (MC) calls for a tricky switching technique based on pulse width modulation, which is prone to commutation failure. The direct frequency conversion using the indirect matrix converter (IMC) with many advantages has appeared as an alternative to these conventional voltage inverters. This study investigates a field-oriented control (FOC) scheme for indirect matrix converter fed triple star induction motor (TSIM). After building the proposed IMC converter topology, an adequate field-oriented control strategy-based space vector modulation (SVM) is proposed and adapted for the control of the triple star induction motor. The FOC technique guarantees flux and torque decoupling while ensuring good operation performance as required in many industrial applications. The obtained numerical simulation results show and confirm the effectiveness of this control scheme.

Direct torque control of induction motor based on sliding mode

Direct torque control of induction motor based on sliding mode

Speed Sensor-less Control of Induction Motor based on Super-helical Sliding Mold

Background: With the continuous progress of technology and the development of shield enterprises, higher requirements are put forward for speed estimation and system stability in the sensorless control system of induction motors in shield machines. Method: In order to solve the problems of velocity observation error and sliding mode vibration of the induction motor velocity observation method based on sliding mold observer, an improved superhelical sliding mold observer is proposed by combining the currently known invention patents and the information based on the induction motor control. Result: The open square of the current error value is introduced into the continuous function of the sliding variable of the observer, and two different functions are used in the boundary layer to replace the sign function, which reduces the sliding mode noise and vibration problems, and the stability of the observer is proved by the Lyapunov stability theory. After that, a phase-locked loop alternative model-referenced adaptive algorithm is used as the rotational speed observation link, which solves the problem that the conventional model-referenced adaptive algorithm relies on the current-modeled magnetic chain observer. Conclusion: The improved super-helical sliding mode observer and phase-locked loop control method effectively reduce the system vibration and speed estimation error of the motor under different speeds and loading conditions, and the observed currents are smoother, which improves the stability of the system. Simulation and experimental results under different working conditions show the effectiveness of the proposed method.

Improved linear/nonlinear active disturbance rejection switching control for bearingless induction motor

ABSTRACT To achieve high-performance operation control for bearingless induction motor (BIM) systems, an improved linear/nonlinear active disturbance rejection switching control strategy is proposed (SADRC). The key innovation lies in the automatic switching between linear and nonlinear control modes based on system stability and disturbance magnitude. First of all, based on the principle of air-gap magnetic field directional control of the BIM, the first-order and second-order ADRC are designed for the rotating and suspending parts of the BIM, respectively. In addition, the nonlinear active disturbance rejection control (NLADRC) has the shortcoming of tracking performance degradation when the disturbance amplitude is large. Then, an active disturbance rejection controller that can automatically switch between linear and nonlinear based on the stability of the system and the magnitude of the disturbance is designed with the introduction of linear active disturbance rejection control (LADRC). The trigonometric function is introduced to improve the fal function to optimise the abrupt change at the linear interval and the high-frequency chattering phenomenon at the origin. The unknown parameters are rectified using the bandwidth method and the particle swarm algorithm, respectively, to ensure the robustness and adaptiveness of the control strategy. Finally, both simulation and experimental results show that the proposed SADRC strategy not only combines the advantages of linear and nonlinear self-anti-disturbance control but also improves the BIM rotor suspension performance and anti-disturbance capability.

Speed Control of a Linear Induction Motor Using V/F Technique

Speed control of single phase Linear Induction Motor using V/F method have been widely used in fans and pumps drives. High-power Linear Induction Motors (LIMs) face challenges in managing speed. Traditional system are ineffective, causing inefficiency and potential damage. To address this, our project proposes a control system for LIM speed control suing V/f method. Currently, linear induction motors (LIMs) are widely used in many industrial applications, including transportation, conveyor systems, actuators, material handling, pumping of liquid metal, sliding-door closers and others, with satisfactory performance. The proposed control system consists of Arduino controller , soft switching for controlling and motor driver board to run Linear induction motor with voltage and frequency monitoring. This control system has almost no effect in normal operation of LIM. Hardware testing results are obtained to verify the valuable operation of proposed circuit in Speed control of LIM. Keywords—Linear Inuction Motor , Speed Control, V/f Method , Arduino Controller , LCD Display etc.

Review and Case Study on Control of Induction Motor Using High-Level Converter

Review and Case Study on Control of Induction Motor Using High-Level Converter

Algebraic Speed Estimation for Sensorless Induction Motor Control: Insights from an Electric Vehicle Drive Cycle

Induction motors (IMs) must meet high reliability and safety standards in mission-critical applications, such as electric vehicles (EVs), where sensorless control strategies are fundamental. However, sensorless rotor speed estimation demands improvements to overcome filtering distortions, tuning complexities, and sensitivity to IM model mismatch. Algebraic methods offer inherent filtering capabilities and design flexibility to address these challenges without introducing additional dynamics into the control system. The objective of this paper is to provide an algebraic estimation strategy that yields an accurate rotor speed estimate for sensorless IM control. The strategy includes an algebraic estimator with single-parameter tuning and inherent filtering action. We propose an EV case study to experimentally evaluate and compare its performance with a typical drive cycle and a dynamic torque load that emulates a small-scale EV power train. The algebraic estimator exhibited a signal-to-noise ratio (SNR) of 43 dB. The closed-loop experiment for the EV case study showed average tracking errors below 1 rad/s and similar performance compared to a well-known sensorless strategy. Our results show that the proposed algebraic estimation strategy works effectively in a nominal speed range for a practical IM sensorless application. The algebraic estimator only requires single-parameter tuning and potentially facilitates IM model updates using a resetting scheme.

AC PWM Control System in Induction Motor using Microcontroller

The demand for efficient and precise control of induction motors has led to the development of advanced control systems, among which AC PWM (Pulse Width Modulation) stands out as a prominent technique. This project focuses on the design and implementation of an AC PWM control system for an induction motor utilizing a microcontroller. The system employs a microcontroller to generate PWM signals, controlling the power electronics responsible for modulating the voltage supplied to the motor. The report details the architecture, components, and methodology employed in the project. A comprehensive discussion on the PWM control algorithm, motor drive circuitry, and sensor integration is presented. The microcontroller programming and experimental results showcase the effectiveness of the proposed system in achieving precise control over motor speed and efficiency. The challenges faced during the project are discussed, along with the corresponding solutions implemented. The report concludes with a summary of achievements and suggestions for future enhancements. Overall, this project contributes to the field of motor control systems, offering a reliable and efficient solution for induction motor control through AC PWM with microcontroller integration

Speed Control of Induction Motors using Neuro Fuzzy Expert Systems

Induction motors and their speed control is critical aspect in several real life applications. Often, the proportional integral derivative (PID) controlling mechanism is found in several applications in industries where speed of motors or induction motors is to be controlled. The PID controller is specifically useful since it tries to minimize the steady state error as well as increase the response or speed of the system, thereby incorporating the benefits of proportional derivative and proportional integral control. However, the real time operation of PID controllers is challenging due to its tuning. The controlling mechanism is critically important for the application of the PID. Previously, manual tuning was used which needed experts and was also prone to errors. With the advent of sophisticated optimization tools, automatic tuning has gained momentum. In this work, a combination of neural networks and fuzzy logic often called neuro fuzzy expert systems has been proposed for the speed control of induction motors. It has been shown that proposed system is capable to attain better results compared to conventional techniques. The system has been designed on Matlab/Simulink. Key Words: Induction Motors, Speed Control, PID Controllers, Fuzzy Logic, Neuro Fuzzy Expert Systems.

Predictive torque control of induction motor for rotor bar faults diagnosis

Unlike DC motors and synchronous motors, they are maintenance-free motors due to the absence of brushes, commutators and slip rings. Induction motors can be operated in polluted and explosive environments as they do not have brushes which can cause sparks. In this paper, the performance of two control techniques, namely direct torque control (DTC) and predictive torque control (PTC), are compared in transient and static states when applied to a faulty induction machine (IM). The current and torque ripples is evaluated in a healthy machine, as well as in the presence of faults, at various speed and load values. During the transient state, the objective is to assess the method that provides the optimal dynamic response, which is achieving the desired speed without any overshooting while during the static state, the objective is to minimize torque ripple and harmonics in the stator current. The Discrete Wavelet Transform (DWT) is used to analyze stator phase current. In addition, the energy eigen value (EEV) analysis has been used to determine the fault severity. The healthy and faulty systems are simulated using Matlab/Simulink for the two control methods. The results show the superiority of the PTC method compared to the DTC. A comparison of the proposed control method with other works reported in the literature is performed to verify the superiority of the proposed strategy.