Search results

To provide a new and simple inverse rotor time constant identification method which can be used to update an indirect rotor field oriented controlled (IRFOC) induction motor algorithm.

Two different equations are used to estimate the rotor flux in the stator reference frame. One of the equations is a function of the rotor time constant, rotor angular velocity and the stator currents. The other equation is a function of measured stator currents and voltages. The equation that uses the voltage and the current signals of the stator serves as reference model, however, the other equation works as an adjustable model with respect to the variation of the rotor time constant. Voltage signals used in the reference model equation are obtained from the measured DC bus voltage and the inverter gating signals. The proposed scheme is verified using a MATLAB/SIMULINK model for two different motors and experimentally using a DSP development tool (MCK 243) supplied by Technosoft S.A.

The proposed estimator was able to successfully track the actual value of the inverse rotor time constant for different load torque and speed operating conditions. Increased oscillations in the estimated inverse rotor time constant appeared at lower speeds (below 10 per cent of rated speed) due to drift in a PI regulator (used at the estimator side), which was tuned under rated operating conditions and using parameters nominal values.

This estimation scheme is limited when near zero speed operation is demanded; otherwise it gives a simple and practical solution. A suggested way out of this, is to provide a self‐tuning controller that can automatically adjust even for zero speed operation, or to automatically disconnect the estimator and take the most updated value as long as the operating speed is below a predetermined value.

This paper presented a new inverse rotor time constant estimator for an IRFOC induction motor application and in conjunction rotor flux was estimated without voltage phase sensors.

The major disadvantage of the field-oriented control (FOC) scheme of induction motors is its dependency on motor parameter variations because of the temperature rise. Among the motor parameters, rotor resistance is a parameter that can degrade the robustness of FOC scheme. An inaccurate setting of the rotor resistance in the slip frequency may result in undesirable cross coupling and performance degradation. To overcome this disadvantage, the purpose of this paper is to propose a model reference adaptive system (MRAS) rotor time constant tuning to improve the induction motor drive performance and to compensate the flux orientation error in vector control law.

First, the dynamic model and the indirect field-oriented control of induction motor are derived. Then, an inverse rotor time constant tuning is proposed based on MRAS theory where a new adaptation signal formulation is used as reference model, and the estimated stator currents obtained from induction motors (IM) state space resolution is used in the adaptive model.

The effectiveness and robustness of IM speed control with the proposed MRAS inverse rotor time constant estimator is verified through MATrix LABoratory/Simulink model simulation and laboratory experimental results. The simulation and experimental results show good transient drive performances, satisfactory for rotor resistance estimation and robustness with regard to uncertainties and load torque disturbance.

This paper presents an online tuning of the inverse rotor time constant using a new adaptation signal MRAS model. The proposed estimator is proved to guarantee the stability for different operating conditions, especially in very low/zero speed region and heavy load torque. The stability analysis of the proposed estimation procedure is also demonstrated.

The end-effects is a well-recognized phenomenon occurring in the linear induction motor (LIM) which makes the analysis and control of the LIM with good performance very difficult and can cause additional significant non-linearities in the model. So, the compensation of parameters uncertainties due to these effects in the control system is very necessary to get a robust speed control. The purpose of this paper is to propose a new technique of LIM end-effects estimation using the inverse rotor time constant tuning in order to compensate the flux orientation error in the indirect field-oriented control (IFOC) control law.

First, the dynamic model of the LIM taking into consideration the end-effects based on Duncan model is derived. Then, the IFOC for LIM speed control with end-effects compensation is derived. Finally, a new technique of LIM end-effects estimation is proposed based on the model reference adaptive system (MRAS) theory using the instantaneous active power and the estimated stator currents vector. These estimated currents are obtained through the solution of LIM state equations.

Simulations were carried out in MATLAB/SIMULINK to demonstrate the effectiveness and robustness of LIM speed control with the proposed MRAS inverse rotor time constant tuning to estimate end-effects value. The numerical validation results show that the proposed scheme permits the drive to achieve good dynamic performance, satisfactory for the estimated end-effects of the LIM model and robustness to uncertainties.

The end-effects causes a drop in the magnetizing, primary and the secondary inductance, requiring a more complex LIM control scheme. This paper presents a new approach of LIM end-effect estimation based on the online adaptation and tuning of the LIM inductances. The proposed scheme use the inverse rotor time constant tuning for end-effects correction in LIM vector control block.

The purpose of this paper aims to design a robust wind turbine emulator (WTE) based on a three-phase induction motor (3PIM).

The 3PIM is driven by a soft voltage source inverter (VSI) controlled by a specific space vector modulation. By adjusting the appropriate vector sequence selection, the desired VSI output voltage allows a real wind turbine speed emulation in the laboratory, taking into account the wind profile, static and dynamic behaviors and parametric variations for theoretical and then experimental analysis. A Mexican hat profile and a sinusoidal profile are therefore used as the wind speed system input to highlight the electrical, mechanical and electromagnetic system response.

The simulation results, based on relative error data, show that the proposed reactive power control method effectively estimates the flux and the rotor time constant, thus ensuring an accurate trajectory tracking of the wind speed for the wind emulation application.

The proposed architecture achieves its results through the use of mathematical theory and WTE topology combine with an online adaptive estimator and Lyapunov stability adaptation control methods. These approaches are particularly relevant for low-cost or low-power alternative current (AC) motor drives in the field of renewable energy emulation. It has the advantage of eliminating the need for expensive and unreliable position transducers, thereby increasing the emulator drive life. A comparative analysis was also carried out to highlight the online adaptive estimator fast response time and accuracy.

The paper sets out to deal with the off‐line identification of induction motor (IM) parameters at standstill. Determination of values of the IM parameters is essential in sensorless drives with regard to accuracy and quality of the control system.

The presented identification method is based on the reconstruction of stator current response to the forced stator voltage step change; thus the cost function is defined in the classical form of the mean squared error between the computed and experimental data. The identification via evolutionary algorithms (EAs) is presented. The considered problem is continuous and thus a continuous version of EA is suggested as more suitable.

This approach has been shown to have several advantages over classical optimisation methods like the ability to cope with ill‐behaved problem domains exhibiting attributes such as: discontinuity, time‐variance, randomness, and, what is particularly important in this application, the ability to cope with the signals disturbed by noises. Owing to this ability the EAs could be implemented directly for the identification of IM parameters not only in simulations but also in the industrial applications for the motor control, though the electrical signals acquired from real motor and used as input data in the identification procedures are to a large extent disturbed by the electrical noises.

Two versions of the suggested approach are compared: the EA with hard selection and with soft selection. Both algorithms were tested in a simulation and experimental set‐up using digital signal processor for control and signal processing of the voltage inverter‐fed IM drive. Satisfactory results were obtained for the identification procedure based on the selected EA.

To meet the need of reducing the cost of industrial systems, sensorless control applications on electrical machines are increasing day by day. This paper aims to improve the performance of the sensorless induction motor control system. To do this, the speed observer is designed based on the combination of the sliding mode and the fractional order integral.

Super-twisting sliding mode (STSM) and Grünwald–Letnikov approach are used on the proposed observer. The stability of the proposed observer is verified by using Lyapunov method. Then, the observer coefficients are optimized for minimizing the steady-state error and chattering amplitude. The optimum coefficients (c₁, c₂, k_i and λ) are obtained by using response surface method. To verify the effectiveness of proposed observer, a large number of experiments are performed for different operation conditions, such as different speeds (500, 1,000 and 1,500 rpm) and loads (100 and 50 per cent loads). Parameter uncertainties (rotor inertia J and friction factor F) are tested to prove the robustness of the proposed method. All these operation conditions are applied for both proportional integral (PI) and fractional order STSM (FOSTSM) observers and their performances are compared.

The observer model is tested with optimum coefficients to validate the proposed observer effectiveness. At the beginning, the motor is started without load. When it reaches reference speed, the motor is loaded. Estimated speed and actual speed trends are compared. The results are presented in tables and figures. As a result, the FOSTSM observer has less steady-state error than the PI observer for all operation conditions. However, chattering amplitudes are lower in some operation conditions. In addition, the proposed observer shows more robustness against the parameter changes than the PI observer.

The proposed FOSTSM observer can be applied easily for industrial variable speed drive systems which are using induction motor to improve the performance and stability.

The robustness of the STSM and the memory-intensive structure of the fractional order integral are combined to form a robust and flexible observer. This paper grants the lower steady-state error and chattering amplitude for sensorless speed control of the induction motor in different speed and load operation conditions. In addition, the proposed observer shows high robustness against the parameter uncertainties.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

To propose and adaptive nonlinear controller for adjustable speed sensorless induction motor drive, using a novel adaptive rotor flux observer. The adaptive flux observer scheme in this paper provides the simultaneous estimation of the rotor speed, rotor resistance and stator resistance.

The IM rotor speed and rotor flux controllers are designed based on combination of input‐output feedback linearizing, linear optimal feedback control and sliding‐mode (SM) control methods. In addition a novel adaptive rotor flux observer is designed based on Lyapunov theory. The proposed control method is tested by simulation and experimental results.

The composite rotor speed and rotor flux observer in combination with adaptive rotor flux scheme guarantees a perfect speed, torque and flux tracking control for the IM sensorless drive.

The proposed control method has a drawback in the IM low speed operating region. Additional research may be able to solve this problem as well as should analyze the sensitivity of the IM drive system performance with respect to variation of the system controller and adaptive flux observer gains. In addition, this research should also analyze the influence of sampling rate, truncation errors, measurement noise, simplifying model assumption and magnetic saturation.

The proposed control method can be used for adaptive and robust control of the IM drive where an optimal efficiency is desired subject to the variable load torque demand.

Based on Lyapunov theory, a novel adaptive rotor flux observer is introduced in which the rotor speed, rotor resistance and stator resistance are treated as the unknown constant parameters.

The purpose of this paper is to discuss the design and verification of a new control algorithm for the drive with permanent magnet synchronous motor (PMSM) and flexible coupling based on “Forced dynamics control”. Control laws are derived and tested for the rotor and load angle control and achieve non‐oscillatory position step response with a specified settling time.

“Forced dynamics control” is a new control technique based on feedback linearization which forces rotor or load position to follow demanded position with prescribed closed‐loop dynamics. The proposed control structure is developed in two steps: first, the feedback linearisation is applied to the rotor speed and then similar technique is used for position control loop.

The proposed controller is of the cascade structure, comprising an inner speed control loop, respecting vector control principles and outer position control loop designed to control the rotor or load angle, respectively. Estimates of load torques acting on the motor and load side as inputs of control algorithms are produced in observers and used to compensate disturbances offering a certain degree of robustness. Preliminary experiments confirm that proposed system follows the ideal closed‐loop dynamics with moderate accuracy.

The focus is on experimental verification of the position control of flexible PMSM drive with two position sensors and moderate precision, where the oscillations due to hardware setup, achieved sampling frequency and corresponding observers adjustment are limited up to 50 rad s⁻¹.

The designed control structure can substantially improve control performance of industrial plants subjects to torsion oscillations.

Experimental results of a novel control structure for the PMSM drives with torsion oscillations are sufficiently promising and confirmed that the rotor and load angle responses follow the prescribed ones fairly closely.

The purpose of this paper is to define a time‐efficient numerical procedure for the extraction of load‐dependent equivalent circuit (EC) parameters of induction machines. The parameters are determined for every operating point, thus their variation due to skin effect and material saturation under arbitrary load condition is taken into consideration.

Two methods are presented and compared. The first one is based on the numerical simulation of the standard measurement process, yielding an EC with constant parameters. A time‐harmonic finite element analysis is applied in the second method to calculate the load‐dependent EC parameters. Material linearization and the superposition principle for the magnetic flux are employed to define the leakage inductances.

A distinct load dependence of all EC parameters has been proven as well as the clear disparity between stator and rotor leakage inductances. These effects can only be taken accurately into account by the EC obtained by the second numerical procedure proposed.

The presented method successfully overcomes typical problems of the measurement process and of the standard numerical procedure for EC parameter estimation, thus the obtained EC parameters are load‐dependent while the physical interpretation of the variables and parameters remains straightforward. Hence, the paper of the internal machine variables is enabled.