Adaptive Flux Observer Research Articles

Input-Output Feedback Linearizing Control Based on the Adaptive Flux Observer of the Induction Motor

In this paper a new technique for the adaptive control of the induction motor is proposed. This technique, which is based on nonlinear control and the adaptive flux observer, maintains the performance of the induction motor. Using this observation technique, the output variables and the unknown parameters estimated by the adaptive flux observer, in the nonlinear control of the induction machine made it possible to achieve remarkable performances. To test the robustness of this control technique, variations of the parameters of the induction machine were applied at different times; the simulation results found confirmed our theoretical study and were very satisfactory with respect to the variation of the parameters.

Sensorless Torque/Speed Control of Induction Motor Drives at Zero and Low Frequencies With Stator and Rotor Resistance Estimations

Stability, robustness, and estimation accuracy of the adaptive flux observer (AFO) for sensorless induction motor (IM) drives are the most critical issues at zero and very low frequencies. In this paper, the design of speed, stator resistance, and rotor resistance estimators, to improve the robustness of AFO to parameters variation, is proposed. These estimators are arranged to have a cascade multi-input multi-output structure, and simplified to a single-input single-output structure for stability analysis and gain selections. To design both the observer feedback gains and adaptive proportional-integral gains, the stability conditions of the estimators are derived to guarantee a stable AFO in all the four quadrants of operation. The sensitivity analysis against stator and rotor resistance variations is also provided. The detailed analytical, simulation, and experimental results are presented to validate the proposed AFO of sensorless IM drives in torque- and speed-controlled modes of operation, particularly at zero and very low frequencies.

Sensorless DTC Drive of Induction Motor Using 3-Level Inverter

This paper presents a novel switching table based Direct Torque Control (DTC) of induction machine modified for the 3-level inverter. Due to its large number of voltage vectors, torque and flux ripples can be reduced by distinguishing small and large torque and flux errors and choosing different switching vectors for each case. This work also introduces two sensor-less DTC systems: the adaptive flux observer and the Model Reference Adaptive System (MRAS). Based on the dynamic model of the induction machine, the adaptive flux observer estimates the rotor flux and speed according to adaptation laws that must ensure the stability of the system. In another hand, the MRAS technique consists on minimizing the error obtained from the comparison of two of rotor flux models, one based on voltage and current and the other based on current and rotor speed, using an adaptive mechanism. The proposed schemes were verified by simulation under Matlab/Simulink environment. Simulation results show good dynamic performances and low ripples of torque response with the employment of 3-level inverter. As for speed estimation, both techniques allow a good estimation of rotor speed, but MRAS technique gives better dynamic performances.

Online Loss-Minimization-Based Adaptive Flux Observer for Direct Torque and Flux Control of PMSM Drive

This paper presents a novel adaptive flux observer based direct torque and flux control (DTFC) of a permanent magnet synchronous motor (PMSM) drive. An online loss minimization algorithm (LMA) is developed to estimate the air-gap flux so that the motor operates at minimum loss condition while taking the general advantages of the DTFC scheme over the conventional vector control scheme. The proposed DTFC-based PMSM drive incorporating the LMA-based flux observer is implemented in real time using the DSP board DS1104 for a laboratory 5-hp motor. The performance of the proposed LMA-based DTFC control of the PMSM drive is tested in both simulation and experiment at different operating conditions.

Characteristics of Speed Sensorless Vector Controlled Induction Motor with High Efficiency Taking Core Loss into Account

This paper presents the characteristics of a speed sensorless vector control method of an induction motor operating at high efficiency and high response, in which core loss is taken into account. An improved method of speed estimation that operates on the principle of speed adaptive flux and current observer has been proposed. An observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltage and current. Simulation results show that the proposed direct field oriented control with the proposed observer provides good performance characteristics. The IM is fed by an indirect power electronics converter. This indirect converter is controlled by a pulse width modulation PWM technique that enables minimization of harmonics introduced by the line converter, as well as the control of the power factor and DC-link voltage. We study the robustness of the overall system- using simulation of different modes to operating modes and varied parameters.

English

Direct torque control is used over Field oriented control (FOC) because of its simple control structure and in steady state, transient state operating conditions shows better torque control. Direct torque control has the advantages like robust and fast torque responsive. But in low speed operation stator flux estimation raises difficulty due to improper working of an open loop voltage model observer and existence of an open loop integrator. Hence an adaptive flux observer is implemented which eliminates open loop integration, therefore improves the machine performance by minimizing stator current distortions, fast response of rotor speed, stator flux electro-magnetic torque without ripple, constant switching frequency. Voltage distortions are modelled using a non-linear inverter. In this paper a novel approach is seen where fuzzy logic controller is adapted which overcomes high torque ripples and improves the system performance. Simulation results are carried out for the proposed system.

An adaptive flux observer for the permanent magnet synchronous motor

SummaryA gradient descent‐based nonlinear observer for surface‐mount permanent magnet synchronous motors with remarkable stability properties was recently proposed. A key assumption for the derivation of the observer is the knowledge of the electrical parameters, which are usually uncertain. In the present paper, we propose a robust adaptive flux observer adding immersion and invariance parameter adaptation algorithms to estimate the stator resistance. Global boundedness of all signals and convergence to a residual set of the flux estimation error is guaranteed. The performance of the new adaptive observer is assessed with realistic simulations. Copyright © 2015 John Wiley & Sons, Ltd.

Аdaptive flux observer for permanent magnet synchronous motors

The paper deals with the observer design problem for a flux in permanent magnet synchronous motors. It is assumed that some electrical parameters such as resistance and inductance are known numbers. But the flux, the angle and the speed of the rotor are unmeasurable. The new robust approach to design an adaptive flux observer is proposed that guarantees globally boundedness of all signals and, moreover, exponential convergence to zero of observer error between the true flux value and an estimate obtained from the adaptive observer. The problem of an adaptive flux observer design has been solved with using the trigonometrical properties and linear filtering which ensures cancellation of unknown terms arisen after mathematical calculations. The key idea is the new parameterization of the dynamical model containing unknown parameters and depending on measurable current and voltage in the motor. By applying the Pythagorean trigonometric identity the linear equation has found that does not contain any functions depending on angle or angular velocity of the rotor. Using dynamical first-order filters the standard regression model is obtained that consists of unknown constant parameters and measurable functions of time. Then the gradient-like estimator is designed to reconstruct unknown parameters, and it guarantees boundedness of all signals in the system. The proposition is proved that if the regressor satisfies the persistent excitation condition, meaning the “frequency-rich” signal, then all errors in observer exponentially converges to zero. It is shown that observer error for the flux explicitly depends on estimator errors. Exponential convergence of parameter estimation errors to zero yields exponential convergence of the flux observer error to zero. The numerical example is considered.

Improved sensorless direct torque control method using adaptive flux observer

A simple structure and a quick and robust response of the direct torque control (DTC) makes it attractive in ac drives. However, in sensorless applications, a precise estimation of the rotor speed is a crucial issue as along with the torque and flux estimation. In this paper an adaptive flux observer is introduced with a stator current and flux vector components as state variables and rotor speed as an unknown parameter which is estimated by using an adaptive scheme. A non-linear inverter model is proposed to obtain a more accurate response. Also, torque, flux and current pulsations, during the steady-state conditions, are considered as the disadvantages of the classical DTC method. A combined DTC and space vector modulation strategy is presented by using fuzzy logic control (FLC). FLCs are designed to obtain a fast response in the transients, and a high accuracy during the steady-state conditions.

Improved Adaptive Flux Observer of an Induction Motor with Fast Lyapunov Optimization Method

In this paper, we propose an improved scheme of adaptive flux observer for the direct field-oriented control of induction motor based on a new fast Lyapunov optimization method to make the estimation of rotor resistance estimation. The improved adaptive flux observer is already presented in other work and based by adding the estimation of the estimation of load torque to the conventional adaptive observer scheme.The fast Lyapunov optimization method is based on using a new concept of Lyapunov function that not based only to guaranty the stability but also the accelerate the convergence of estimation of rotor resistance of induction motor.The performances of the proposed adaptive observer were verified with numerical simulation. The obtained results show the effectiveness of the new fast Lyapunov 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.

Sensorless Stator Field-Oriented Controlled IM Drive at Low Speed withRrEstimator

This paper pertains to a technique of a sensorless indirect stator field-oriented induction motor control, which prevents the accumulative errors incurred by the integrator and the problem relating to the stability of the control system caused by the stator resistance susceptible to temperature variations while conducting the flux estimation directly and computing the synchronous rotary speed. The research adds an adaptive flux observer to estimate the speed of the rotor and uses the fixed trace algorithm (FTA) to execute an online estimation of the slip difference, thereby improving the system of stability under the low rotary speed at regenerating mode and the influence of the rotor resistance on the slip angle. Finally, the paper conducts simulations by Simulink of MATLAB and practices to verify the correctness of the result the paper presents.

Design and Implementation of Adaptive Fuzzy Cerebellar Model Articulation Controller for Direct Torque Control System

This study implemented fuzzy control theory with a cerebellar controller to design a fuzzy cerebellar model articulation controller (FCMAC), ensuring system stability by deriving an adaptive FCMAC weight update rule from the Lyapunov theory. The speed estimator design in this study is based on the structure of an adaptive stator flux observer (ASFO) to achieve rapid sensorless control. According to results from experiments, installing the adaptive FCMAC speed controller in the induction motor’s direct torque control system demonstrates excellent speed dynamic response.

Rotor Speed and Stator Resistance Identification Scheme for Sensorless Induction Motor Drives

This paper proposes a rotor speed identification method for sensorless induction motor drives based on a model reference adaptive system (MRAS). In this scheme, the error between estimated stator current and real stator current is regarded as the system error to estimate the rotor speed. Adaptive full-order flux observers for estimating the rotor speed are developed using Lyapunov’s stability theory. The stator resistance identification algorithm is developed with rotor speed estimating method in a systematic manner. Because of the stator resistance varies with inner temperature of the motor, the influence of motor speed estimation due to stator resistance identification error is analyzed. The error compensation method for stator resistance estimation is also proposed. Simulation and experimental results show the good performance for the proposed scheme in speed and robustness for sensorless induction motor drives. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.1865

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.

Direct field oriented control scheme for space vector modulated AC/DC/AC converter fed induction motor

This paper investigates a Luenberger flux observer with speed adaptation for a direct field oriented control of an induction motor. An improved method of speed estimation that operates on the principle of speed adaptive flux and current observer has been proposed. An observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltage and current. Simulation results show that the proposed direct field oriented control with the proposed observer provides good performance dynamic characteristics. The induction motor is fed by an indirect power electronics converter. This indirect converter is controlled by a sliding mode technique that enables minimization of harmonics introduced by the line converter, as well as the control of the power factor and DC-link voltage. The robustness of the overall system is studied using simulation for different operating modes and varied parameters.

Study on the Cooperative Control of the Power Generation System and an Electric Power Compensatory System in Micro Grid

We have proposed a method to cooperative control both fly wheel energy storage system (FWES) and micro gas turbine (MGT) electrical generation system in micro grid system because the capacity of the electric power storage equipment used for electric power compensation is desirable to have low capacity as much as possible from the viewpoint of cost. The speed information of FWES is necessary in order to perform the cooperative control. When system composition is considered, it is desirable to use a speed observer instead of a rotoring speed sensor from the viewpoint of cost and maintenance side. Therefore, the adaptive rotor flux observer is proposed in of this paper. And the validity of adaptive rotor flux observer is confirmed by the simulation.

Stability Analysis of Speed and Stator Resistance Estimators for Sensorless Induction Motor Drives

This paper presents an analysis by which the stability of a multiple-input-multiple-output system of simultaneous speed and stator resistance estimators for sensorless induction motor drives can be successfully predicted. The instability problem of an adaptive flux observer (AFO) is deeply investigated. In order to achieve stability over a wide range of operation, a design of the observer feedback gain is proposed. Furthermore, closed-loop control systems of the independent use of the two estimators are developed. Therefore, all gains of the adaptive proportional-integral controllers are selected and generalized to provide good tracking performance as well as fast dynamic response. The performance of the AFO using the proposed gains, with a sensorless indirect-field-oriented-controlled induction motor drive, is verified by simulation and experimental results. The results show a good improvement in both convergence and stability, particularly in the regenerative mode at low speeds, which confirm the validity of the proposed analysis.

Research on Adaptive Rotor Flux Observer with the Speed Feedback and Rotor Resistance Disturbing

Rotor flux observation is a key step in implementation of a field-oriented vector control system. Aiming at eliminating the influence of the actual speed fluctuation and rotor resistance variety, an adaptive rotor flux observer was proposed to accurately estimate the flux of induction motors in modern high performance drivers, based on the conception of close-loop flux estimation and the extended state observer theory. The performance of the proposed scheme is verified through simulation and experiment.

A Novel Identification Method of Rotor Time Constant of Induction Motor

Vector control system is dependent of parameters of motor, and rotor time constant usually changes with temperature. Through analyzing the influence of rotor time constant variations on the control system performance, a novel identification method based on adaptive flux observer is presented. Different with traditional pole assignment method, it implies robust control theory and Lyapunov stability theory, by solving a linear matrix inequality (LMI) to obtain the feedback gain matrix. The simulation results show that this method can identify the rotor time constant of induction motor accurately, and it has rapid converge, good indiscrimination degree and strong robustness.