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The paper describes field-oriented control strategy with space vector pulse width modulation technique of permanent magnet synchronous motor drive system for an electric vehicle. At first, mathematical models of the motor and the drive system for electric vehicle are presented. In order to obtain high performance drive and maximum motor torque, field-oriented control strategy and space vector pulse width modulation technique method are applied to drive system in next section. Speed controller design utilizing the popular zero-pole elimination approach causes large integral constant time in case of small rotational damping constant. The desired-transient-responsebased approach is employed to overcome the problem. Performance indices include overshoot, undershoot, steady-state speed error, and total harmonic distortion of stator current, are employed to assess the drive systems with two speed controller design methods. Theoretical assumptions are confirmed via simulations and criteria in MATLAB/Simulink environment.

This paper presents first results and test of passive detection of Digisonde signal obtained at the Průhonice station, Czech Republic. Described technique can be used to analyze signals transmitted by the Digisonde and further received by simple loop antenna. The receiving system is based on the software defined radio (SDR USRP N210). The device works as the two channels receiver. This method will be employed to record oblique ionograms at several locations in the Czech Republic forming a simple array for detection of fine structures within ionospheric plasma using common DPS 4D transmitter. Using relatively inexpensive passive detection helps to increase a number of reflection points which leads to a better spatial coverage of the ionosphere sounding. The device represents a complementary measurement for detection of signal transmitted by Digisondes in European sector.

This paper deals with a novel method to achieve the effective performance of the extended Kalman filter (EKF) for the speedy estimate of an induction motor. The real coding genetic algorithm (GA) is used to optimize the components of the covariance matrix in the EKF, thus ensuring the stability and accuracy of the filter in the speed estimation. The advantage of the proposed method is less dependent on the parameters of the induction motor. The content includes the vector control model for induction motor, the speed estimation by modeling the reference frame-model reference adaptive system (RF-MRAS), the current based-model reference adaptive system (CB-MRAS), and the speed estimation with the EKF optimized by genetic algorithm. Simulative studies on the field-oriented controller (FOC) with different operating conditions are performed in Matlab Simulink when the rotor resistance changes in the current speed estimation methods. The simulation results demonstrate the efficiency of the proposed GA-EKF filter compared with other speed estimation methods of induction motors.

The paper presents an application of sliding mode controller and Kalman Filter (KFSMC) in speed control of pulse-width-modulation direct torque controlled induction motor drive. The performance of the direct torque control (DTC) is degraded by the uncertainty of stator resistance. In order to increase the robustness of the controlled system to the uncertainty, a sliding mode controller (SMC) is utilized to replace the proportional-integral (PI) speed controller in the conventional DTC drive structure. Computation of SMC requires estimation of load, and Kalman Filter is integrated to reduce noise in load estimation and chattering phenomenon in speed response. Simulations are carried out at different reference speeds in a wide range of noises of stator resistance. Indices including ITAE, settling time, overshoot, and undershoot are employed to compare the performance of drive structures. Results confirmed the desired characteristics of the proposed drive structure.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

This paper describes an induction motor speed estimation using the observer with back electromotive force-based model reference adaptive system and Kalman filter. In the first part of the paper, there is a mathematical description of the rotor speed observer. The second part of the paper includes Kalman filter that is used for the filtration of measured stator currents and obtaining their time derivatives. The third part contains a description of the laboratory workplace with the induction motor drive and active load unit that was used for an experimental verification of the rotor speed observer. The last section of the paper shows experimental results that were obtained for different changes in the induction motor speed. The experimental results confirmed expected dynamic properties of the induction motor drive with sensorless control.

Induction motors are widely used in an industry and it is necessary to improve control methods for induction motors to increase the efficiency of them. In this paper, sliding mode controllers are proposed instead of traditional PI controllers in vector control of induction motor drives. Moreover, rotor speed is estimated by a sliding mode observer. In addition, the robustness of control and observer algorithms are also proved by Lyapunov’s criterion. The experiments are obtained in different speed changes of an induction motor drive. These experimental results confirm the dynamic properties of a sensorless sliding mode control of an induction motor drive.

The paper presents an improving speed control method using a field-oriented control (FOC) technique for the hysteresis current (HC) controller in the induction motor drive. The basic principle of a controller applying hysteresis band current is comparing reference currents and the measured currents to generate switching pulses for controlling an inverter. In the typical FOC for the HC controller, the rotor flux angle’s value will increase to infinity due to the integral algorithm’s error accumulation. This problem can lead to the faulty operation of the induction motor drive (IMD) system. In this paper, a current model with the advantage of precisely determining the periodic rotor flux angle is used in the FOC technique to provide reference currents for the current controller. The rotor flux angle will periodically change according to the motor speed in the range [-π π] during the operation of IMD. The operation of the induction motor drive is implemented and tested by MATLAB/SIMULINK software. The simulation results have demonstrated the effectiveness of the HC control method-based FOC technique with periodic rotor flux angle in controlling motor speed. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

The paper deals with application of Kalman filter in induction motor drive using pulse-width modulation direct torque control (PWM-DTC). In the first part, the conventional PWM-DTC drive is described and Kalman filter is utilized to filter components of stator current vector those are assumed to be disturbed by white noise. The second part contains simulation results that are obtained in different cases of load torque, process and measurement noise covariances. The integral time absolute error (ITAE) performance index, undershoot, ripple of important quantities are used to compare the conventional drive structure and proposed drive structure with Kalman filter. The simulation results confirm the expected dynamic response of the proposed structure. &nbsp

During last years, sensorless control is one of the most favorite field in control of AC machines, especially induction motor drives. Sensorless control means that an encoder is replaced by estimated speed from an observer or an estimator. Sensorless control reduces cost and increases the reliability of the system. However, the accuracy of the observer or estimator depends on induction motor parameters. In this paper, the robust sliding mode observer with estimated rotor and stator resistances is investigated. The proof of stability of the algorithm is also presented. The robust sliding mode observer is verified through simulations and experiments with an induction motor drive. Some of control methods such as PI control and sliding mode control are used in the experiments.

The paper describes observers using model reference adaptive system for sensorless induction motor drive with the pulse width modulator and the direct torque control under the circumstances of incorrect information of induction motor parameters. An approximation based on the definition of the Laplace transformation is used to obtain initial values of the parameters. These values are utilized to simulate sensorless control structures of the induction motor drive in Matlab-Simulink environment. Performance comparison of two typical observers is carried out at different speed areas and in presence of parameter uncertainty. A laboratory stand with the induction motor drive and load unit is set up to verify the properties of observers. Experimental results confirm the expected dynamic properties of selected observer. Web of Science 16 4 434 426

The paper describes a fuzzy speed controller with direct torque control for induction motor drive. Classical PI speed controller with fixed proportional and integral coefficients is not appropriate for exact motor speed regulation in a wide range of reference speed. Fuzzy logic, one of simplest soft computing techniques, can make PI controllers more flexible. In the paper, a simple fuzzy algorithm is proposed for online update coefficients of PI speed controller. The use of a pulse-width modulator in the direct torque control structure is to ensure the constant switching frequency. The control structures of the induction motor drive are implemented into a control system with digital signal processor. Experimental results confirm that speed controller with proposed fuzzy algorithm gives response of actual motor speed with lower overshoot, shorter settling time, and smaller speed accuracy than classical speed controller does.

The paper describes machine model-based speed observers for speed sensorless induction motor drive with direct torque and flux control. However, the wrong information of machine model, especially stator resistance, affects the performance of the direct torque control. Thus, model reference adaptive system based scheme is developed for adapting stator resistance. At first, the sensorless control structures of the induction motor drive are implemented in Matlab-Simulink environment. Then, comparison is done by evaluation of the rotor speed difference. The simulation results confirm that model reference adaptive system speed observers and adaptation technique in control structures are simple to simulate and experiment. By comparison of speed estimators without and with adaptation technique, current based model reference adaptive system observer and Luenberger observer give higher accuracies of the speed estimation, more robust with uncertainty of stator resistance.

The paper describes speed estimators for a speed sensorless induction motor drive with the direct torque and flux control. However, the accuracy of the direct torque control depends on the correct information of the stator resistance, because its value varies with working conditions of the induction motor. Hence, a stator resistance adaptation is necessary. Two techniques were developed for solving this problem: model reference adaptive system based scheme and artificial neural network based scheme. At first, the sensorless control structures of the induction motor drive were implemented in Matlab-Simulink environment. Then, a comparison is done by evaluating the rotor speed difference. The simulation results confirm that speed estimators and adaptation techniques are simple to simulate and experiment. By comparison of both speed estimators and both adaptation techniques, the current based model reference adaptive system estimator with the artificial neural network based adaptation technique gives higher accuracy of the speed estimation.

The paper deals with a speed estimation of the induction motor using observer with back electromotive force based model reference adaptive system and Kalman filter. The first part of the paper includes the mathematical description of the rotor speed observer. The second part describes Kalman filter that is used for the filtration of measured stator currents and obtaining their time derivatives. The third part describes a laboratory stand with the induction motor drive and active load unit that was used for an experimental verification of the rotor speed observer. In the last section of the paper, experimental results are shown for different changes of the induction motor speed which confirm good dynamic properties of the induction motor drive with sensorless control.

The paper describes Model Reference Adaptive System (MRAS) observers for the speed estimation of an induction motor with direct torque and flux control. The first estimator is a reference frame MRAS (RF-MRAS) and the second estimator is a current based MRAS (CB-MRAS). At first, direct torque controlled induction motor drive with two estimators are implemented on Matlab-Simulink environment. Then, comparison of two observers is done by evaluation of the rotor speed difference. The simulation results confirm that both MRAS estimators are simple to simulate and experiment. By comparison of both observers, the CB-MRAS observer gives higher accuracy of the rotor speed estimation.

Stability range of proportional (P) controllers can be obtained using Routh-Hurwitz criterion for continuous linear time invariant (LTI) control systems or Bistritz criterion, Jury criterion for discrete LTI systems. Conditions from these criterions bring out inequalities. In case of high-order plants, these inequalities are very difficult to solve directly. In the paper, an algorithm is developed on MATLAB software to solve polynomial inequalites. With the support of this algorithm, stability criterions are implemented to find stability range of P controllers.

This paper presents an induction motor drive using a method of direct torque and stator flux control. One disadvantage of the algorithm is a variable switching frequency of a voltage source inverter although it is used a constant period for the direct torque control processing in a digital signal controller. It is difficult to carry out a good filtration of the variable switching frequency; therefore it finally leads to higher level of interference. It is possible to avoid the problem and ensure the constant switching frequency of the voltage source inverter by the application of a pulse-width modulator in the control structure of the induction motor drive. In the paper it is described basic mathematical equations of the direct torque control of the induction motor and it is shown simulation results which confirm theoretical assumptions of the induction motor drive properties.