Flux Observer Of Induction Motor Research Articles

СПОСТЕРІГАЧ ПОТОКОЗЧЕПЛЕННЯ, АДАПТИВНИЙ ДО ЗМІН АКТИВНОГО ОПОРУ РОТОРА АСИНХРОННИХ ДВИГУНІВ

A flux observer for induction motors which is adaptive to the active rotor resistance variations is presented. Due to the added fluxes overestimation in the observer structure, the global exponential stability properties of the current and flux vector components and active rotor resistance estimation are ensured under conditions of persistency of excitation. The proposed observer has a simpler structure compared to existing solutions with the global stability properties. The simulation results of the observer dynamic performance investigation confirm its effectiveness. It is shown that even if the conditions of persistency of excitation are not met, the active rotor resistance is estimated correctly; consequently, the designed observer can be implemented as an identification algorithm in self-commissioning systems of induction electric drives. References 9, figures 5.

Novel Direct Torque Control Based on Space Vector Modulation with Adaptive Stator Flux Observer for Induction Motors using ANFIS

Novel Direct Torque Control Based on Space Vector Modulation with Adaptive Stator Flux Observer for Induction Motors using ANFIS

A Speed and Flux Observer of Induction Motor Based on Extended Kalman Filter and Markov Chain

To improve the performance of sensorless induction motor (IM) drives, an adaptive speed and flux estimation method based on the multiple-model extended Kalman filter (EKF) with Markov chain for IMs is proposed in this paper. In this algorithm, the multiple model EKF for speed and flux estimation is established, and the transition of the models obeys the Markov chain and the estimation value is obtained by mixing the outputs of different models in different weightings, and the calculation of the weighting is researched. Simultaneously, the transition probability can be continuously self-tuned by the residual sequence, the prior information is modified by the posterior information, and the more accurate transition among the models is obtained. Therefore, the proposed method improves the model adaptability to the actual systems and the environmental variations, and reduces the speed estimation error. The correctness and the effectiveness of the proposed method are verified by the simulation and experimental results.

Optimal Tuning of PI Controller for Full-Order Flux Observer of Induction Motor Using the Immune Genetic Algorithm

This paper presents a new method to tune the parameters of the adaptation PI controller of full-order flux observer. The method employs an Immune Genetic Algorithm (IGA) based optimization routine that can be implemented off-line. A novel fitness function is designed to assess both the estimation accuracy and the noise sensitivity of the rotor speed estimation system when each antibodys parameters are employed. The diversity of population is guaranteed by the evaluating of the antibody similarities function. The Roulette-wheel selection is used to choose the parents and large mutation probability is adopted to prevent the evolution from prematurity. The simulation results verify that the IGA has better performance in convergence speed and computation efficiency compared to the traditional GA.

Stator Flux Observer for Induction Motor Based on Prescribed Convergence Law Algorithm

This paper proposes a stator flux estimation method for induction motor based on Prescribed Convergence Law algorithm. A stator flux observer is designed and applied for direct torque control (DTC) of induction motor. The observer tracks stator current and its differential with Prescribed Convergence Law algorithm of second order sliding mode in order to estimate rotor flux, and then estimate stator flux using the relationship between stator flux and rotor flux. This paper takes the differential of estimated flux error as disturbance and divides the MIMO (Multiple Input Multiple Output) observer model into two separate SISO (single input single output) systems, which simplifies the stability analysis. The observer is applied to DTC of induction motor and achieves a good control effect. Simulation experiment results validate the proposed method.

Enhanced adaptive flux observer for induction motor drive system with mutual inductance adjustment

In this paper, an enhanced scheme of adaptive flux observer of induction motor with mutual inductance adaptation is proposed. This adaptive observer is used with direct field-oriented control of induction machine. It is based on using induction motor model with the estimation of the load torque besides the estimation of the mutual inductance. The robustness of this observer with respect to the mutual inductance variations is studied. The obtained results show performance of estimation and adaptation of mutual inductance using the new adaptive flux observer.

High Performance of Self Scheduled Linear Parameter Varying Control with Flux Observer of Induction Motor

This paper deals with a robust controller for an induction motor (IM) which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI) based approach and robust Lyapunov feedback are associated. This approach is related to the fact that the synthesis of a linear parameter varying (LPV) feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a polytopic LPV system because of speed and rotor resistance affine dependence. Their values can be estimated on line during systems operations. The simulation and experimental results largely confirm the effectiveness of the proposed control.

Stator Flux Observer for Induction Motor Based on Tracking Differentiator

Voltage model is commonly used in direct torque control (DTC) for flux observing of asynchronous motor. In order to improve low-speed and dynamic performance of the voltage model, a modified low-pass filter (LPF) algorithm is proposed. Firstly, the tracking differentiator is brought in to modulate the measured stator current, which suppresses the measurement noise, and then amplitude and phase compensation is made towards the stator electromotive force (EMF), after which the stator flux is obtained through a low-pass filter. This method can eliminate the dynamic error of flux filtered by LPF and improve low-speed performance. Experimental results demonstrate effectiveness and improved dynamic performance of such method.

Cascaded Nonlinear Adaptive Predictive Control based Adaptive Flux Observer of Induction Motor

his paper present a new advanced control algorithm based on continuous minimization of predicted tracking errors, to achieve torque, rotor speed and rotor flux amplitude tracking objectives. This algorithm called a new Adaptive Nonlinear Predictive Control to induction motor drive uses a combination of the adaptive observer for rotor flux and Cascaded Nonlinear Predictive Control technique. The variables to be controlled are the rotor speed and the rotor flux norm, required to implement the predictive control algorithm is estimated by flux observer. The parameters identified adaptively are stator and rotor resistance which vary with motor temperature using the adaptive rotor flux observer. A stability of the proposed adaptive flux observer will be proved by the Lyapunov's theorem. Simulations are carried out in order to show the effectiveness of the drive and the robustness to parameters variations.

A New Flux Observer for Induction Motors with On-Line Identification of Load Torque and Resistances

AbstractUnder the assumption that the stator currents and voltages are available from measurements along with the rotor speed, a novel local adaptive flux observer for induction motors is presented which, under persistency of excitation, estimates the motor fluxes and identifies on-line the rotor resistance. A sufficiently slow adaptation for the stator resistance is performed in order to isolate its estimation from the estimation of motor fluxes and rotor resistance. A second-order load torque identifier is also designed to be used in conjunction with the adaptive flux observer and the stator resistance identifier. The advantages of the proposed observer with respect to previous work are: the assumption of bounded stator currents integrals is no longer required; the dynamic order of the adaptive flux observer is reduced to six; a clear physical interpretation of the persistency of excitation condition is given. On the other hand the convergence analysis of the error dynamics holds only locally under suitable identifiability conditions while globally convergent algorithms are available in the literature.

Novel Direct Torque Control Based on Space Vector Modulation With Adaptive Stator Flux Observer for Induction Motors

This paper describes a combination of direct torque control (DTC) and space vector modulation (SVM) for an adjustable speed sensorless induction motor (IM) drive. The motor drive is supplied by a two-level SVPWM inverter. The inverter reference voltage is obtained based on input-output feedback linearization control, using the IM model in the stator D-Q axes reference frame with stator current and flux vectors components as state variables. Moreover, a robust full-order adaptive stator flux observer is designed for a speed sensorless DTC-SVM system and a new speed-adaptive law is given. By designing the observer gain matrix based on state feedback H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control theory, the stability and robustness of the observer systems is ensured. Finally, the effectiveness and validity of the proposed control approach is verified by simulation results.

Adaptive sliding mode observer for induction motor using two-time-scale approach

This paper presents an original method for the design of a robust adaptive sliding mode current and flux observer for induction motor drive using two-time-scale approach. This approach, based on the singular perturbation theory, decomposes the original system of the observer error dynamics into separate slow and fast subsystems of lower dimensions and permits a simple design and sequential determination of the observer gains. For the proposed observer, the rotor speed signal is assumed to be available. The stator currents and rotor flux are observed on the stationary reference frame using sliding mode concept, and the adaptive rotor time-constant is derived from Lyapunov stability theory using measured and estimated currents and estimated rotor flux. The control algorithm is based on the indirect field-oriented sliding mode control to keep the machine field oriented. The control-observer scheme seeks to provide asymptotic tracking of speed and rotor flux in spite of the presence of an uncertain load torque and unknown value of the rotor resistance. The effectiveness of this control algorithm has been successfully verified through computer simulations.

A hybrid speed estimator of flux observer for induction motor drives

This paper proposes a hybrid speed estimator that gives the synergetic effect between the model- and the saliency-based field orientations for induction motor drives. The model-based field orientation consists of a flux observer with an adaptive speed estimator that has unstable regions at zero frequency and zero speed. Saliency-based flux orientation utilizes magnetic saliencies caused by saturation and high-frequency injection that causes the torque ripples due to the chattering. The chattering is caused by the higher cutoff frequency of the flux-angle estimation to keep its high dynamics. The proposed method compensates both faults and realizes complete speed estimation from zero to high-speed condition including zero stator frequency.

Flux observer with online tuning of stator and rotor resistances for induction motors

This paper proposes an adaptive flux observer for induction motors, where stator and rotor resistances are estimated in online environments. The variation of motor parameters during operation degrades the performance of the controller and the flux observer. Among the parameters of induction motors, rotor resistance is a crucial one for flux estimation, and stator resistance also becomes critical in the low-speed region. Under the persistent excitation condition, the proposed method estimates the actual values of stator and rotor resistances simultaneously, which guarantees the exact estimation of the rotor flux. The persistent excitation condition is not satisfied when the electric torque of an induction motor is absent due to the lack of rotor currents. Even in this case, the proposed method achieves the correct estimation of the rotor flux. Simulations and actual experiments show that the rotor flux is estimated in all operating conditions and that both resistances converge to their actual values when the electrical motor torque exists.

Nonlinear system identification using a neo fuzzy neuron algorithm: electrical drive application.

This work presents a Neo-Fuzzy-Neuron algorithm for the identification of nonlinear dynamic systems at the point of view of a rotor flux observer. The algorithm training is on-line, has low computational cost, does not require previous training and its convergence in one step is proved. The gradient descent method is used for its weights adjustment. Simulation and experimental results demonstrate the effectiveness of the algorithm for flux observer of induction motor drive system.

Adaptive Flux Observer for Induction Motors with Uncertain Stator and Rotor Resistance

A ninth-order adaptive flux observer is designed which, on the basis of rotor speed, stator voltages and stator currents measurements, provides an on-line exponentially convergent estimate of rotor flux when persistency of excitation conditions are satisfied. Under these conditions, both rotor resistance and stator resistance are also asymptotically recovered. The proposed estimation scheme is intended to improve performance and efficiency of currently available induction motor control algorithms.

DSP-based speed adaptive flux observer of induction motor

A method for estimating the rotor flux and speed of an induction motor based on adaptive control theory is presented. The method is applied to a direct field-oriented induction motor control without speed sensors. The influence of the parameter variation on the speed estimation can be removed by the proposed parameter adaptive scheme. The validity of the adaptive flux observer is verified experimentally. >

Adaptive flux observer of induction motor and its stability.

The indirect field oriented control of an induction motor is widely used. This methbd has a disadvantage which is sensitivity to the motor parameter variation. Especially, resistance depends on the motor temperature. On the other hand, the direct field oriented control method is robust against the motor parameter variation because the measured motor flux is fed back to the reference. The disadvantage of this method is that the installation of a flux sensor is necessary. Therefore, flux estimation from the terminal variables is usually used instead of the flux measurement. However, flux estimation is also sensitive to the motor parameter variation.Recently, flux observers have been proposed for flux estimation. The sensitivity of the flux observers to the rotor resistance variation is much lower than that of the conventional flux, estimator. However, the sensitivity of these observers cannot be completely zero.To solve these problems, a new rotor flux observer with parameter adaption scheme is proposed in this paper. Parameters identified adaptively are the stator and rotor resistance which are dependent upon the motor temperature. A stability of the proposed adaptive flux observer is proved by the Lyapunov's theorem.

Adaptive flux observer of induction motor and its stability

The indirect field oriented control of an induction motor is widely used. This methbd has a disadvantage which is sensitivity to the motor parameter variation. Especially, resistance depends on the motor temperature. On the other hand, the direct field oriented control method is robust against the motor parameter variation because the measured motor flux is fed back to the reference. The disadvantage of this method is that the installation of a flux sensor is necessary. Therefore, flux estimation from the terminal variables is usually used instead of the flux measurement. However, flux estimation is also sensitive to the motor parameter variation.Recently, flux observers have been proposed for flux estimation. The sensitivity of the flux observers to the rotor resistance variation is much lower than that of the conventional flux, estimator. However, the sensitivity of these observers cannot be completely zero.To solve these problems, a new rotor flux observer with parameter adaption scheme is proposed in this paper. Parameters identified adaptively are the stator and rotor resistance which are dependent upon the motor temperature. A stability of the proposed adaptive flux observer is proved by the Lyapunov's theorem.