无轴承异步电机无速度传感器控制

为解决无轴承异步电机运行中转速辨识问题,提出了一种可以同时在线估计转子电阻和转速的方法。该方法首先通过电压型转子磁链模型估计出转子磁链,然后根据静止坐标系下的无轴承异步电机模型和电压型转子磁链模型推出包含转子电阻和转速的表达式,再将这两个表达式看作一个二元一次方程组并求解,最终得到转子电阻跟转速的解析表达式。最后应用这种转速估计方法构建无轴承异步电机无速度传感器控制系统,并开展仿真研究。仿真结果表明:所提方法能够实现无轴承异步电机转子电阻和转速的准确估计,并保证无轴承异步电机的稳定悬浮运行。     

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.     

Speed-sensorless vector control of an induction motor using neuralnetwork speed estimation

In this paper, a novel speed estimation method of an induction motor using neural networks (NNs) is presented. The NN speed estimator is trained online by using the error backpropagation algorithm, and the training starts simultaneously with the induction motor working. The estimated speed is then fed back in the speed control loop, and the speed-sensorless vector drive is realized. The proposed NN speed estimator has shown good performance in the transient and steady states, and also at either variable-speed operation or load variation. The validity and the usefulness of the proposed algorithm are thoroughly verified with experiments on fully digitalized 2.2 kW induction motor drive systems     

Implementation and experimental investigation of sensorless speed control with initial rotor position estimation for interior permanent magnet synchronous motor drive

In this paper, a new approach to sensorless speed control and initial rotor position estimation for interior permanent magnet synchronous motor (IPMSM) drive is presented. In rotating condition, speed and rotor position estimation of IPMSM drive are obtained through an extended Kalman filter (EKF) algorithm simply by measurement of the stator line voltages and currents. The main difficulty in developing an EKF for IPMSM is the complexity of the dynamic model expressed in the stationary coordinate system. This model is more complex than that of the surface PMSM, because of the asymmetry of the magnetic circuit. The starting procedure is a problem under sensorless drives, because no information is available before starting. The initial rotor position is estimated by a suitable sequence of voltage pulses intermittently applied to the stator windings at standstill and the measurement of the peak current values of the current leads to the rotor position. Magnetic saturation effect on the saliency is used to distinguish the north magnetic pole from the south. To illustrate our work, we present experimental results for an IPMSM obtained on a floating point digital signal processor (DSP) TMS320C31/40 MHz based control system.     

Initial rotor position estimation method of sensorless PMsynchronous motor with no sensitivity to armature resistance

This paper proposes a new initial rotor position estimation method of a sensorless permanent magnet (PM) synchronous motor at starting condition, which has no sensitivity to the armature resistance. The method is based on saliency of the rotor and employs the alternating magnetic field which is excited by a current controller. The phase differences between the magnetizing current references and the voltage references make it possible to estimate the rotor direction accurately without motor parameters, except the ratio of direct axis and quadrature axis inductance. Also, the magnetic pole is evidently identified by detecting the voltage reference oscillation phenomena caused by magnetic saturation, which can be performed without motor parameters. The experimental result has proven that the estimation error was within -4.5 to +2.5 mechanical degrees, even though the armature resistance varied to 125% of the nominal value     

Performances of bearingless and sensorless induction motor drive based on mutual inductances and rotor displacements estimation

A self-sensing bearingless motor is considered as an effective solution to reduce cost and shorten a shaft length. In this paper, a novel estimation method of a rotor displacement is proposed. The method is based on the detection of currents induced by mutual inductances, which vary as a function of the rotor displacements. A high-frequency carrier voltage is superimposed on a motor main terminal voltage. The induced carrier-frequency current component is distinguished from the suspension-winding current. The carrier signal is selected high enough to suspension-current components. However, the carrier current is disturbed in transient conditions. The disturbed current results in a vibration of the estimated rotor displacements. A suspension-current estimator is proposed to reduce this vibration and to obtain the difference between the detected current and the estimated current. As a result, the disturbance vibration is significantly reduced. It is shown that a successful magnetic suspension is realized with the proposed method.     

High-performance induction motor speed control using exact feedback linearization with state and state derivative feedback

This paper presents a novel nonlinear speed/position control strategy for the induction motor utilizing exact feedback linearization with state and state derivative feedback. The speed/position and flux control loops utilize nonlinear feedback which eliminates the need for tuning, while ordinary proportional-integral controllers are used to control the stator currents. The control scheme is derived in rotor field coordinates and employs an appropriate estimator for the estimation of the rotor flux angle, flux magnitude, and their derivatives. The overall control scheme can be easily implemented with a microprocessor-based control platform. An error sensitivity analysis is included which proves the system to be robust to parameter variation and even more, immune to rotor resistance variation. Simulation and experimental results validate the theoretical part of the paper and reveal the high performance and advantages of the novel control scheme.     

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     

基于滑模控制的异步电机无速度传感器DTC研究

建立了一种滑模速度观测器,用于电机转速的精确观测。该观测器充分利用电机状态方程具有的结构特点,设计出简单有效的速度估算方法,在转子磁链的估算中无须用到转子时间常数和转速等信息,提高了观测器对于参数误差的鲁棒性。将所建立的观测器和空间电压矢量脉宽调制技术(SVPWM)结合对电机进行控制,进一步提高了系统的调速性能。仿真结果验证了基于滑模控制理论的异步电机无速度传感器直接转矩控制系统的可行性以及对参数误差的鲁棒性。     

Nonlinear adaptive speed and torque control of induction motorswith unknown rotor resistance

In this paper, we propose a nonlinear adaptive speed and torque controller of induction motors with unknown rotor resistance. All the system parameters except rotor resistance are assumed to be known, and only the stator currents and rotor speed are assumed to be available. The desired speed and torque should be a smooth bounded function. A complete proof of the global stability without singularity is given, and the output error will converge to zero asymptotically. Finally, the simulation and experimental results are given to demonstrate the effectiveness of the proposed controller     

Adaptive speed control for induction motor drives using neuralnetworks

In this paper, the adaptive speed control of induction motor drives using neural networks is presented. To obtain good tracking and regulating control characteristics, a digital two-degree-of-freedom (2DOF) controller is adopted and a design procedure is developed for systematically finding its parameters according to prescribed specifications. The parameters of the controller corresponding to various drive parameter sets are found off-line and used as the training patterns to estimate the connection weights of neural networks, Under normal operation, the true drive parameters are real-time identified and they are converted into the controller parameters through multilayer forward computation by neural networks. The parameters of the 2DOF controller can be adapted to match the desired specifications under various operating conditions     

A start-up method for a speed sensorless stator-flux-orientedvector-controlled induction motor drive

This paper describes a zero-speed start-up method of a speed sensorless stator-flux-oriented direct vector-controlled induction motor drive with the help of a machine current model that does not use any speed signal. The machine starts smoothly with vector control at finite developed torque and then transitions to the standard direct vector-control mode with the voltage model signals as the speed begins to develop. The direct vector-control mode with voltage model uses programmable cascaded low-pass filters for flux-vector synthesis and enables the drive to operate from zero speed to field-weakening mode. As the drive speed falls to zero, the drive again transitions to start-up mode, so that it can be smoothly started again. The performance of the start-up scheme has been verified on a 100 kW electric vehicle drive     

Low-frequency signal-demodulation-based sensorless technique for induction motor drives at low speed

The paper presents a method to compute the air-gap flux position in induction motors at very low including zero-stator frequency. A low-frequency (50 /spl divide/ 100 Hz) sinusoidal stationary signal is added to the normal stator variables to provide the machine with a suitable permanent excitation. Such an additional excitation modulates the saturation level of the magnetic core of the machine according to the angular position of the air-gap flux. As a result, a new zero-sequence stator-voltage component is generated that contains useful information about the position of the air-gap flux unaffected by load variation. Such a zero-sequence voltage can be easily employed to provide a wide bandwidth measurement of the air-gap flux position. A key feature of the proposed approach is that a low-frequency (0 /spl divide/ 5 Hz) signal is demodulated, thus avoiding any drawback featured by previous sensorless techniques operating with high-frequency signal injection.     

An effective method for rotor resistance identification forhigh-performance induction motor vector control

An effective method for rotor resistance identification is presented for the purpose of improving the performance of vector control of induction motor drives. The method is mathematically derived from proper selection of coordinate axes and utilization of the steady-state model of the induction motor. The major advantages of the method lie in its simplicity and accuracy. A series of computer simulations has been performed with very satisfactory results     

Hybrid rotor position observer for wide speed-range sensorless PM motor drives including zero speed

This paper addresses the problem of wide speed-range sensorless control of a surface-mount permanent-magnet (SMPM) machine including zero-speed operation. A hybrid structure integrating a flux observer and signal-injection techniques is proposed, which results in a rotor position signal independent of motor parameters at low and zero speed. Although the SMPM machine typically has a very low geometric saliency, the injection technique is effective in tracking the saturation-induced saliency produced by the stator flux. Experimental results are presented showing an excellent performance for both the sensorless speed and position control using an off-the-shelf SMPM machine.     

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     

Accurate rotor position detection and sensorless control of SRM for super-high speed operation

Based on the general nonlinear magnetizing model (GNMM) from our previous research work, an improved method of detecting rotor position for sensorless control of SRMs in super-high speed operation has been developed. With minimum input data, the approximated GNMM is obtained and the rotor speed estimated. Then the rotor position is detected by the motion equation. To remove rotor position error, the proposed scheme updates the reference at critical points using the flux observation. Further, the GNMM is adaptively tuned based on the updated information. The improved rotor position detection method has been implemented by fully exploring the computation power of the modern DSP. Laboratory verification on different types of SRMs with sensorless control up to 20000 rpm is accomplished.     

Sliding-mode MRAS speed estimators for sensorless vector control of induction Machine

This paper presents two novel sliding mode (SM) model reference adaptive system (MRAS) observers for speed estimation in a sensorless-vector-controlled induction-machine drive. Both methods use the flux estimated by the voltage model observer as the reference and construct SM flux observers that allow speed estimation. Stability and dynamics of the two proposed SM flux observers are discussed. The observers are compared with the classical MRAS observer. The proposed estimators seem very robust and easy to tune. Unlike the classical MRAS, the speed-estimation process is based on algebraic calculations that do not exhibit underdamped poles or zeros on the right-hand plane. Simulations and experimental results on a 1/4-hp three-phase induction machine confirm the validity of the approaches.     

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.