A MRAS-based adaptive pseudoreduced-order flux observer for sensorless induction motor drives

The performance of vector-controlled sensorless induction motor drives is generally poor at very low speeds, especially at zero speed due to offset and drift components in the acquired feedback signals, and the increased sensitivity of dynamic performance to model parameter mismatch resulting especially from stator resistance variations. The speed estimation is adversely affected by stator resistance variations due to temperature and frequency changes. This is particularly significant at very low speeds where the calculated flux deviates from its set values. Therefore, it is necessary to compensate for the parameter variation in sensorless induction motor drives, particularly at very low speeds. This paper presents a novel method of estimating both the shaft speed and stator resistance of an induction motor. In this novel scheme, an adaptive pseudoreduced-order flux observer (APFO) is developed. In comparison to the adaptive full-order flux observer (AFFO), the proposed method consumes less computational time, and provides a better stator resistance estimation dynamic performance. Both simulation and experimental results confirm the superiority of the proposed APFO scheme for a wide range of resistance variations from 0 to 100%.     

A new current model flux observer for wide speed range sensorless control of an induction machine

A new closed loop current model flux observer is designed to estimate the rotor flux, position and velocity of an induction machine. The current observer includes carefully designed sliding mode functions which are derivative of the fluxes along the /spl alpha/ and /spl beta/ axes. Therefore, when the estimated current converges to the measured one, the flux estimation is a mere integration of the sliding mode function. The rotor speed can then be derived from the sliding mode functions and the estimated flux. In the current and flux observers all of the terms that contain the rotor time constant and the rotor speed have been replaced by the sliding mode functions, thus making the proposed current and flux estimations completely insensitive to the rotor time constant variation and any error in the estimated speed. Simulations and experiments are performed under a variety of conditions to validate the effectiveness of the proposed algorithm.     

Lyapunov-function-based flux and speed observer for AC induction motor sensorless control and parameters estimation

AC induction motors have become very popular for motion-control applications due to their simple and reliable construction. Control of drives based on ac induction motors is a quite complex task. Provided the vector-control algorithm is used, not only the rotor speed but also the position of the magnetic flux inside the motor during the control process should be known. In most applications, the flux sensors are omitted and the magnetic-flux phasor position has to be calculated. However, there are also applications in which even speed sensors should be omitted. In such a situation, the task of state reconstruction can be solved only from voltage and current measurements. In the current paper, a method based on deterministic evaluation of measurement using the state observer based on the Lyapunov function is presented. The method has been proven in testing on a real ac induction machine.     

Stabilization of regenerating-mode operation in sensorless induction motor drives by full-order flux observer design

This paper deals with the full-order flux observer design for speed-sensorless induction motor drives. An unstable region encountered in the regenerating mode at low speeds is well known. To remedy the problem, a modified speed-adaptation law is proposed. Instead of using only the current estimation error perpendicular to the estimated flux, the parallel component is also exploited in the regenerating mode. Using current estimation error loci in steady state, a linearized model, simulations, and experiments, it is shown that the observer using the proposed speed-adaptation law does not have the unstable region. It is also shown that the effect of erroneous parameter estimates on the accuracy of the observer is comparatively small.     

An improved flux observer based on PLL frequency estimator for sensorless vector control of induction motors

This paper presents an improved method of flux estimation for sensorless vector control of induction motors based on a phase locked loop (PLL) programmable low-pass filter (LPF) and a vector rotator. A PLL synchronized with the voltage vector is used for stator frequency estimation. The pure integration of the stator voltage equations is difficult to implement and LPFs with a fixed cutoff provide good estimates only in the relatively high frequency range-at low frequencies, the estimates fail in both magnitude and phase. The method proposed corrects the above problem for a wide range of speeds. Simulations and experimental results on a 0.25-hp three-phase induction machine verify the validity of the approach.     

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.     

Observers for flux estimation in induction machines

Flux estimation in induction machines is examined from the viewpoint of observer theory. It is pointed out that estimators presently used in connection with schemes such as field-oriented control are typically real-time simulations of machine equations, without feedback of any corrective prediction error. It is shown that corrective feedback can be used to speed up convergence of the flux estimates. It can also reduce the sensitivity of the estimates to parameter variations     

A new EKF-based algorithm for flux estimation in induction machines

A reduced-order algorithm for estimating the rotor flux components of induction motors with schemes such as field-oriented control is described. The algorithm is based on the extended Kalman filter (EKF) theory and estimates the desired quantities online using only measurements of the stator voltages and currents and the rotor speed. The online adaptation of the inverse rotor time constant makes it possible to obtain very accurate estimates of rotor flux components, in spite of temperature and magnetic saturation effects. The algorithm order reduction decreases the computational complexity and makes the proposed estimator superior to others based on EKF theory     

Speed sensorless vector control of induction motor usingKalman-filter-assisted adaptive observer

This letter presents a new method of estimating rotor speed of an induction motor. The new method is based on an adaptive flux observer. A second-order Kalman filter is then employed to modify the estimated rotor flux. Experimental results show that the new method has better accuracy in following the speed command under heavy loads     

Analysis and design of full-order flux observers for sensorless induction motors

This paper deals with the flux estimation for sensorless induction motor drives. The linearized model of the speed-adaptive full-order flux observer is applied to help choosing the observer gain and the speed-adaptation gains. It is shown that the linearized model reveals potential instability problems that are difficult to find by other means. An observer gain and a method to vary the speed-adaptation gains in the field-weakening region are proposed. Experimental results show stable operation in a very wide speed range.     

A high-performance sensorless indirect stator flux orientation control of induction motor drive

A new method for the implementation of a sensorless indirect stator-flux-oriented control (ISFOC) of induction motor drives with stator resistance tuning is proposed in this paper. The proposed method for the estimation of speed and stator resistance is based only on measurement of stator currents. The error of the measured q-axis current from its reference value feeds the proportional plus integral (PI) controller, the output of which is the estimated slip frequency. It is subtracted from the synchronous angular frequency, which is obtained from the output integral plus proportional (IP) rotor speed controller, to have the estimated rotor speed. For current regulation, this paper proposes a conventional PI controller with feedforward compensation terms in the synchronous frame. Owing to its advantages, an IP controller is used for rotor speed regulation. Stator resistance updating is based on the measured and reference d-axis stator current of an induction motor on d-q frame synchronously rotating with the stator flux vector. Experimental results for a 3-kW induction motor are presented and analyzed by using a dSpace system with DS1102 controller board based on the digital signal processor (DSP) TMS320C31. Digital simulation and experimental results are presented to show the improvement in performance of the proposed method.     

Current sensorless position–flux tracking controller for induction motor drives

An innovative indirect field-oriented output feedback controller for induction motor drives is presented. This solution is based on output feedback since only speed and position of the motor shaft are measured, while current sensors are avoided. This approach is suitable for low cost applications, where the position sensor cannot be removed to guarantee accurate position tracking.The proposed method provides global asymptotic tracking of smooth position and flux references in presence of unknown constant load torque. It is based on the natural passivity of the electromagnetic part of the machine and it guarantees asymptotic decoupling of the induction motor mechanical and electrical subsystems achieving at the same time asymptotic field orientation. Lyapunov analysis and nonlinear control design have been adopted to obtain good position tracking performances and effective torque–flux decoupling. The cascaded structure of the controller allows performing a constructive tuning procedure for speed and position control loops.Results of experimental tests are presented to demonstrate the tracking and robustness features of the proposed solution.     

A sensorless vector control system for induction motors usingq-axis flux with stator resistance identification

This paper presents a sensorless vector control system for general-purpose induction motors, which is based on the observer theory and the adaptive control theories. The proposed system includes a rotor speed estimator using a q-axis flux and stator resistance identifier using the d-axis flux. The advantages of the proposed system are simplicity and avoidance of problems caused by using only a voltage model. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including the influence of the observer gain, motor operating state, and parameter variations. In order to obtain stable low-speed operation and speed control accuracy, an algorithm for compensating for the deadtime of the inverter and correcting the nonideal features of an insulated gate bipolar transistor was developed. The effectiveness of the proposed system has been verified by digital simulation and experimentation     

An improved stator flux estimation for speed sensorless stator fluxorientation control of induction motors

This paper proposes a programmable low pass filter (LPF) to estimate stator flux for speed sensorless stator flux orientation control of induction motors. The programmable LPF is developed to solve the DC drift problem associated with a pure integrator and a LPF. The pole of the programmable LPF is located far from the origin in order to decrease the time constant with the increasing speed. In addition, the programmable LPF has a phase/gain compensator to estimate exactly stator flux in a wide speed range. Consequently, the drift problem is much improved and the stator flux is exactly estimated in the wide speed range. The validity of the proposed programmable LPF is verified by speed sensorless vector control of a 2.2 kW three-phase induction motor     

基于改进型滑模观测器的永磁同步电机控制

传统基于反电动势的滑模观测器采用Sign函数来作为开关函数,因为Sign函数的开关特性,使系统存在抖振大的问题。在传统滑模观测器的基础上,通过采用Sigmoid函数代替Sign函数,改善了开关特性,大大地减少了抖振,并去掉了滤波器和转角补偿器,简化了系统,提高了反电动势的估算精度,从而得到更精确的转速和转角位置信息。在Matlab/Simulink平台基础上建立控制系统仿真模型,对该方案做了验证。仿真结果表明:该方法提高了滑模观测器的精度,降低了系统的抖振,提高了系统的性能。     

A nonlinear state observer for the sensorless control of apermanent-magnet AC machine

This paper presents a sensorless speed regulation scheme for a permanent-magnet synchronous motor (PMSM) based solely on the motor line currents measurements. The proposed scheme combines an exact linearization-based controller with a nonlinear state observer which estimates the rotor position and speed. Moreover, the stability of the closed-loop system, including the observer, is demonstrated through Lyapunov stability theory. The proposed observer has the advantage of being insensitive to rotation direction. It is shown how a singularity at zero velocity appears in the scheme and how it can be avoided by switching smoothly from the observer-based closed-loop control to an open-loop control at low velocity. The system performance is tested with an experimental setup consisting of a PMSM servo drive and a digital-signal-processor-based controller for both unidirectional and bidirectional speed regulation     

New sensorless vector control using minimum-order flux state observer in a stationary reference frame for permanent-magnet synchronous motors

This paper proposes a new sensorless vector control method that can be applied to both of salient-pole and nonsalient-pole permanent-magnet synchronous motors (PMSMs). The proposed method estimates the phase of a rotor flux by a newly developed state observer in a stationary reference frame for sensorless vector controls of PMSMs. The flux state observer has the following attractive features: 1) it requires no steady-state conditions for the dynamic mathematical model of the motor; 2) its order is the minimum second; 3) a single observer gain is simply constant over a wide operating range and can be easily designed; 4) it utilizes motor parameters in a very simple manner; and 5) its structure is very simple and can be realized at a very low computational load. The proposed speed-estimation method, which exploits the inherent physical relation of integration/derivation between phase and speed, is very simple and can properly estimate rotor speed. The usefulness of the proposed method is examined and confirmed through extensive experiments.     

A nonlinear momentum observer for sensorless robot collision detection under model uncertainties

Collision detection methods could reduce collision forces and improve safety during physical human-robot interaction without additional sensing devices. However, current collision detection methods result in an unavoidable trade-off between sensitivity to collisions, peaking value reduction near the initial time, and immunity to measurement noise. In this paper, a novel nonlinear extended state momentum observer (NESMO) is proposed for detecting collisions between a robot body and human under model uncertainties based on only position and current measurements. The collision detection method is divided into three steps. The first step is to identify the robot dynamic model. Then, we can deduce the generalized momentum-based state-space equations from the identified base dynamic parameters. The second step is to construct a NESMO. Benefiting from the fractional power function and the time-varying damping ratio, the NESMO achieves the required monitoring bandwidth with noise immunity. The last step is to design a novel time-varying threshold (TVT) to distinguish the collision signal from the estimated lumped disturbance. As with the dynamic model parameters, the coefficients of TVT could be obtained by offline identification. Combined with NESMO, the method can provide timely and reliable collision detection and estimation under model uncertainties. Simulation and experimental results obtained using a 6-DOF robot manipulator illustrate the effectiveness of the proposed method.     

A position-and-velocity sensorless control for brushless DC motorsusing an adaptive sliding mode observer

The sliding mode observer is robust to measurement noises. Since the switching signals of the sliding mode observer contain the induced voltages of the motors, it is possible to obtain the position and velocity of the motors directly from the switching signals. Although the estimated position can be used for locating the position of the rotor, the estimated velocity is heavily contaminated by noises from the switching signals. This direct method nullifies the merit of the sliding mode observer. Thus, the authors also present an adaptive scheme for robust estimation of the velocity of brushless DC motors. Stability of the adaptive scheme is assured, and estimation errors due to parameter deviations are analyzed. A method of parameter adjustment is described     

Speed sensorless stator flux-oriented control of induction motor in the field weakening region using Luenberger observer

In a conventional speed sensorless stator flux-oriented (SFO) induction motor drive, when the estimated speed is transformed into the sampled-data model using the first-forward difference approximation, the sampled-data model has a modeling error which, in turn, produces an error in the rotor speed estimation. The error included in the estimated speed is removed by the use of a low pass filter (LPF). As the result, the delay of the estimated speed occurs in transients by the use of the LPF. This paper investigates the problem of a conventional speed sensorless SFO system due to the delay of the estimated speed in the field weakening region. In addition, this paper proposes a method to estimate exactly speed by using Luenberger observer. The proposed method is verified by the simulation and experiment with a 5-hp induction motor drive.