Earticle

This paper presents a speed sensorless control strategy for full-scale converter of wind turbine with the squirrel-cage induction generator (SCIG) based on a Model Reference Adaptive System (MRAS) method. The full-scale converter wind turbine has many advantages, such as simple structure, high reliability, low maintenance cost. However, there are still some drawbacks in its traditional control strategy, such as control stability, system performance, efficiency and reliability. The project implementation about generator speed estimation based on MRAS method is studied, and DC bias suppression is described completely based on the characteristics of SCIG. The Simulation experimental results show a consistency that is mainly in the correctness of flux observer design, the effectiveness of speed sensorless implementation strategy and good static and dynamic properties in the system.

This paper presents a novel sensorless control method of permanent magnet synchronous motors at standstill and low speed based on a low-frequency current signal injection. The approach superimposes a persistent LF current signal into the estimated d-axis to get the rotor position error angle-related signal by detecting the corresponding voltage response and current response. Then the rotor position and motor speed are obtained. Theoretical analysis and simulation results demonstrate that the approach can achieve sensorless control of permanent magnet synchronous motors at zero and low speed, ensure good dynamic and static performances, and achieve effective control when applied to servo system. Finally, a test prototype system which used a digital signal processor and space vector pulse width modulation technology has been developed. Experimental results show that the system has better static, the effectiveness and dynamic performance of the adaptive test signals in a sensorless controlled surface-mounted permanent magnet synchronous machines.

This paper presents a novel sensorless control method of permanent magnet synchronous motors at standstill and low speed based on a low-frequency current signal injection. The approach superimposes a persistent LF current signal into the estimated d-axis to get the rotor position error angle-related signal by detecting the corresponding voltage response and current response. Then the rotor position and motor speed are obtained. Theoretical analysis and simulation results demonstrate that the approach can achieve sensorless control of permanent magnet synchronous motors at zero and low speed, ensure good dynamic and static performances, and achieve effective control when applied to servo system. Finally, a test prototype system which used a digital signal processor and space vector pulse width modulation technology has been developed. Experimental results show that the system has better static, the effectiveness and dynamic performance of the adaptive test signals in a sensorless controlled surface-mounted permanent magnet synchronous machines.

This paper focuses on a sensorless control method for small wind turbines based on permanent magnet synchronous generators. An adaptive intelligent algorithm is proposed to estimate the rotor speed for designing sensorless controllers of small wind turbines. In the proposed algorithm, a model reference adaptive system has been formed by using the instantaneous and steady-state powers to estimate the rotor speed. Then a power speed feedback (PSF) control carries out maximum power point tracking by using the optimum relationship between speed and power, which is kept in a lookup table. The efficiency of the system is improved by vanishing the observation errors and tracking errors. The validity of the proposed algorithm is verified by the simulation results.

This paper presents a hybrid sensorless control for an interior permanent magnet synchronous motor (IPMSM) for zero-, low-, and high-speed regions. Many sensorless control methods such as an observer-based estimator have been introduced. However, most of the observer-based estimators have a disadvantage at start-up and in the low-speed region. To solve this problem, a simple strategy of using a hybrid system is proposed by integrating a high-frequency (HF) signal injection method and a full-order flux observer. In addition, an HF signal injection method with only a low pass filter (LPF) is proposed to simplify the hybrid system. The hybrid system achieves high-performance drive throughout the entire speed range. The effectiveness of the proposed hybrid technique is verified by experiments using an 11-kW IPMSM drive system.

This paper investigates the application, design and implementation of unscented Kalman filter observer using the various scaling parameters for the sensorless speed control of a permanent magnet synchronous motor. The principles of unscented transformation and unscented Kalman filter are examined and their applications are explained. Typically the mapping transformation process is divided into two types, namely the basic unscented transformation and the general unscented transformation by virtue of the scaling parameter value. And resultantly, the number of sampling points, weights, code configuration and computation time are different. But there is no little information on the scaling parameter value or how this value influences the system performance. To analyze the unscented transformation with the various scaling parameters in this study, the experimental results under a wide range of operation condition have been demonstrated.

A robust adaptive speed sensorless induction motor direct torque control (DTC) using a neural network (NN) is presented in this paper. The inherent lumped uncertainties of the induction motor DTC system such as parametric uncertainty, external load disturbance and unmodeled dynamics are approximated by the NN. An additional robust control term is introduced to compensate for the reconstruction error. A control law and adaptive laws for the weights in the NN, as well as the bounding constant of the lumped uncertainties are established so that the whole closed-loop system is stable in the sense of Lyapunov. The effect of the speed estimation error is analyzed, and the stability proof of the control system is also proved. Experimental results as well as computer simulations are presented to show the validity and efficiency of the proposed system.

A new method of induction motor drive, which requires neither shaft encoder nor speed estimator, is presented. The proposed scheme is based on decreasing current gap between a numerical model and an actual motor. By supplying the identical instantaneous voltage to both model and motor in the direction of reducing the current difference. the rotor approaches to the model speed. that is. reference value. The indirect field orientation algorithm is employed for tracking the model currents. The performance of induction motor drives without speed sensor is generally characteristic of poorness at very low speed. However, in this system, it is possible to obtain good speed response in the extreme low speed range.

This paper proposes a sensorless speed control algorithm for parallel-connected dual Surface-mounted Permanent Magnet Synchronous Motors (SPMSMs) fed by a single inverter. For stable parallel operation of synchronous motors with a single inverter, each motor has to be constantly kept in the synchronization state regardless of load torque. If the master motor with the larger load is controlled, the synchronous state will be maintained. Therefore, detection of the master motor is essential. Conventionally, the master motor is determined by comparing the rotor position error from the relation between the back-EMF for torque angle and the flux position; consequently, the position sensor is deemed essential for finding the rotor position. The parallel sensorless speed control method proposed in this paper uses no position sensor, instead it compares the flux-axis current from the connection between the back-EMF for torque angle and current in unbalanced load conditions. The results of simulation and experiment conducted verify the efficacy of the proposed method.

PMSMS (permanent magnet synchronous motors) are widely used in industrial applications and home appliances because of their high torque to inertia ratio, superior power density, and high efficiency. For high performance control, accurate informations about the rotor position is essential. Sensorless algorithms have lately been studied extensively due to the high cost of position sensors and their low reliability in harsh environments. A novel position sensorless speed control for PMSMs uses indirect flux estimation and is presented in this paper. Rotor position and angular velocity are estimated by the proposed indirect flux estimation. Linkage flux and magnetic field flux are calculated by the voltage equations and the measured phase current without any integration. Instead of linkage flux calculation with integral operation, indirect flux and differential magnetic field are used for the estimation of rotor position. A proper rejection technique fur current noise effect in the calculation of differential linkage flux is introduced. The proposed indirect flux detecting method is free from the integral rounding error and linkage flux drift problem, because differential linkage flux can be calculated without any integral operation. Furthermore, electrical parameters of the PMSM can be measured by the proposed TCM (time compression method) for soft starting and precise estimation of rotor position. The position estimator uses accurate electrical parameters that are obtained from the proposed TCM at starting strategy. In the operating region, a proper compensation method fur temperature effect can compensate fir the estimation error from the variation of electrical parameters. The proposed novel position sensorless speed control scheme is verified by the experimental results.

This work proposes a highly efficient sensorless motor driver chip for various permanent-magnet synchronous motors (PMSMs) in a wide power range. The motor driver chip is composed of two important parts. The digital part is a sensorless controller consisting mainly of an angle estimation block and a speed control block. The analog part consists of a gate driver, which is able to sense the phase current of a motor. The sensorless algorithms adapted in this paper include a sliding mode observer (SMO) method that has high robust characteristics regarding parameter variations of PMSMs. Fabricated SMO chips detect back electromotive force signals. Furthermore, motor current-sensing blocks are included with a 10-bit successive approximation analog-to-digital converter and various gain current amplifiers for proper sensorless operations. Through a fabricated SMO chip, we were able to demonstrate rated powers of 32 W, 200 W, and 1,500 W.

The noise covariance matrices Q and R are set as constant values in the traditional extended Kalman filter (TEKF). They are determined by trial and error. This process is very complicated and the optimal matrices are difficult to determine. In addition, when the characteristic of noise changes, the matrices cannot be adjusted correspondingly, and the performance of the TEKF deteriorates. Therefore, an adaptive EKF algorithm based on the maximum likelihood estimation criterion with limited memory exponential weighting (EW-MLE-AEKF) is proposed in this paper. In the proposed EW-MLE-AEKF algorithm, the windowing method is adopted to save the posterior residual sequences in the previous N calculation periods. Then, these sequences are used to estimate and update the process noise covariance matrix Q in real time. To speed up the convergence speed of the estimation, a limited memory exponential weighting algorithm is added to the windowing method, which can increase the importance of recent data. Through real-time experiments, the superiority of the proposed EW-MLE-AEKF algorithm is verified.

Speed sensorless control systems with a full order adaptive observer of the permanent magnet synchronous motor (PMSM) have received wide attention due to their advantages of simple structure, easy implementation and strong universality. However, they are sensitive to the load disturbances, which affects the speed performance of the control system. To solve this problem, this paper presents a disturbance rejection speed sensorless control of PMSMs based on full order adaptive observer to improve robustness against load disturbances. A load disturbance observer (LDO) is used to observe load disturbances, which feed-forward compensates the q-axis current to reduce the speed drop and accelerate the recovery time. Experimental results show that the proposed method has better anti-interference capability than full order adaptive speed sensorless control under the same steady-state performance.

In induction machine drive without a speed sensor, the estimation of the motor flux and speed often becomes deteriorated at low speeds with low back EMF. Our analysis shows that, in addition to the state resistance variation, the estimated value of field orientation angle is often corrupted by accumulative errors from the integration of voltage variables at motor terminals that have low signal/noise ratio at low frequencies. A repetitive loop path of integration in the feedback can amplify this type of error, thus speeding up the degradation process. The control system runs into information starvation due to the loss of correct field orientation. The machine's spiral vectors are controlled only in a reduced dimension in this situation. A novel control scheme is developed to improve the control performance of motor's current, torque and speed at low frequencies. The scheme gains a full-dimensional vector control and is less sensitive to the combined effect of the error sources at the low frequencies. Experimental tests demonstrate promising performances are achievable even below 0.5 Hz.

This study describes the scheme of vector drive system without speed sensor for AC servo motor using theory of a flux observer and based on the field oriented vector control. The new method of speed estimation is presented from operate with the position and magnitude of the secondary flux which obtain from the voltage reference and detected current. As the estimated speed is settled by the flux and the machine-specific parameters. this method don't need to adjust the gain of the parameter. Based on the derived theory for vector control. the scheme for sensorless vector drive of AC servo motor is designed and realized. And the experiment verifies it passable to realize the sensorless vector drive based on a field-oriented type.

This paper is on realization of the speed-sensorless vector control of an induction motor using the RLS(Recursive Least Square) algorithm. The speed estimator is including the RLS algorithm and a rotor flux observer. The RLS algorithm has speed and rotor time constant as parameter vectors and rotor flux observer is designed to have robustness to stator resistance variation and through the IP(Integral and Proportional) speed controller stable performance is obtained for estimating rotor speed. Finally the total algorithm are realized in induction motor drive system and its effectiveness is verified.