Hybrid Terminal Sliding-Mode Observer Design Method for a Permanent-Magnet Synchronous Motor Control System

This paper proposes a hybrid terminal sliding-mode observer based on the nonsingular terminal sliding-mode (NTSM) and the high-order sliding-mode (HOSM) for the rotor position and speed estimation in the permanent-magnet synchronous motor control system. An NTSM manifold is utilized to realize both fast convergence and better tracking precision. In addition, a derivative estimator is used to obtain the derivative of the sliding-mode function. Meanwhile, an HOSM control law is designed to guarantee the stability of the observer and eliminate the chattering, so that smooth back-electromotive-force (EMF) signals can be obtained without a low-pass filter. According to the back-EMF equations, the rotor position and speed of the motor can be calculated. Simulation and experimental results are presented to validate the proposed method.      

Exponentially convergent rotor resistance estimation for inductionmotors

A new estimation algorithm is presented which provides exponential estimation of rotor resistance for induction motor drives in physical operating conditions. The exponential convergence is not influenced by the value assumed by rotor speed, including zero speed. The algorithm also provides flux estimates and may be viewed as an adaptive observer. Experimental results show good performance with a sampling time of 0.8 ms which makes the algorithm implementable on-line by available digital signal processors     

A rotor position and speed observer for permanent-magnet motors with nonsinusoidal EMF waveform

A new nonlinear reduced-order observer to estimate the rotor speed and position for permanent-magnet motors, with arbitrary electromotive force (EMF) waveform, is presented. The proposed observer is suitable for the realization of a torque control with minimum torque ripple. In order to implement the observer, the EMF generated by the motor is first obtained experimentally offline. After that, it is approximated by a Fourier series in order to develop the model to be used in the online estimation. From the estimated EMF, rotor position and speed are calculated using the relationship between the EMF and the rotor variables. The proposal is validated with experimental results.     

基于龙贝格观测器的PMSM无位置传感器控制系统设计

针对基于低分辨率霍尔位置传感器的永磁同步电机系统在中高速时出现的估算精度低与响应速度慢等问题,在建立永磁同步电机数学模型的基础上,将龙贝格观测器与锁相环结构相结合,提出一种永磁同步电机无位置传感器控制算法。利用MATLAB/Simulink工具搭建控制系统仿真模型验证该控制系统的可行性,并通过搭建基于PAC5232的实物平台对比验证龙贝格观测器相对于霍尔位置传感器的优越性。实验结果表明,该无位置传感器控制系统有效地提高了系统的响应速度和估算精度,使其能够更好地跟踪转子速度以及转子位置信息。     

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.     

Disturbance and nonlinear Luenberger observers for estimating mechanical variables in permanent magnet synchronous motors under mechanical parameters uncertainties

This paper deals with rotor position and speed estimation of permanent-magnet synchronous motors. Two reduced-order observers, a disturbance observer and a nonlinear one, are considered. It is shown that under exact model assumption the nonlinear observer converges in an exponential way, while a residual estimation error appears when the disturbance observer is used. Therefore, uncertainties in the mechanical submodel are taken into account. Estimation error arises due to the model mismatch; bounds for this error are calculated in both observers. Finally, a comparison of the performance of each observer is presented.     

Instantaneous power control of a high speed permanent magnet synchronous generator based on a sliding mode observer and a phase locked loop

This paper proposes an instantaneous power control method for high speed permanent magnet synchronous generators (PMSG), to realize the decoupled control of active power and reactive power, through vector control based on a sliding mode observer (SMO), and a phase locked loop (PLL). Consequently, the high speed PMSG has a high internal power factor, to ensure efficient operation. Vector control and accurate estimation of the instantaneous power require an accurate estimate of the rotor position. The SMO is able to estimate the back electromotive force (EMF). The rotor position and speed can be obtained using a combination of the PLL technique and the phase compensation method. This method has the advantages of robust operation, and being resistant to noise when estimating the position of the rotor. Using instantaneous power theory, the relationship between the output active power, reactive power, and stator current of the PMSG is deduced, and the power constraint condition is analysed for operation at the unit internal power factor. Finally, the accuracy of the rotor position detection, the instantaneous power detection, and the control methods are verified using simulations and experiments.     

Comparative study of adaptive and inherently sensorless observers for variable-speed induction-motor drives

State observers are key components of modern ac drives. The paper presents a comparative analysis of two state observers for induction-motor (IM) drives: the speed-adaptive observer and the inherently sensorless observer. The adaptive observer employs the time-variable full-order motor model with the rotor speed as the adaptive quantity. Thus, the speed estimation accuracy significantly impacts on the flux observer. It is shown that the popular model reference adaptive system (MRAS) speed estimator displays reduced bandwidth, and does not deliver adequate performance for the flux estimation. The inherently sensorless observer employs a full-order dual reference-frame model in order to eliminate the speed adaptation. In this way, it becomes decoupled from the speed estimator and its performance is superior to that of its adaptive counterpart. Theoretical aspects and comparative simulation results are discussed for both observers. Comparative experimental results for both observers are presented. Very low-speed-operation (3 r/min) capability of the drive with the sensorless observer is demonstrated.     

Position sensing in brake-by-wire callipers using resolvers

Recent designs for brake-by-wire systems use "resolvers" to provide accurate and continuous measurements for the absolute position and speed of the rotor of the electric actuators in brake callipers (permanent magnet DC motors). Resolvers are absolute-angle transducers that are integrated with estimator modules called "angle tracking observer" and together they provide position and speed measurements. Current designs for angle-tracking observers are unstable in applications with high acceleration and/or speed. In this paper, we introduce a new angle-tracking observer in which a closed-loop linear time-invariant (LTI) observer is integrated with a quadrature encoder. Finite-gain stability of the proposed design and its robustness to three different kinds of parameter variations are proven based on theorems of input-output stability in nonlinear control theory. In our experiments, we examined the performance of our observer and two other methods (a well-known LTI observer and an extended Kalman filter) to estimate the position and speed of a brake-by-wire actuator. The results show that because of the very high speed and acceleration of the actuator in this application, the LTI observer and Kalman filter cannot track the rotor position and diverge. In contrast, with a properly designed open-loop transfer function and selecting a suitable switching threshold, our proposed angle-tracking observer is stable and highly accurate in a brake-by-wire application.     

Sensorless vector control of synchronous reluctance motors withdisturbance torque observer

The elimination of the position sensor has been one important requirement in vector control systems because the position sensor spoils the reliability and simplicity of drive systems. Therefore, we present a sensorless vector control technique for synchronous reluctance motors. The rotor position is calculated easily from ds-qs-axes flux linkages which are estimated with a first-order lag compensator. Furthermore, utilizing estimated rotor position as the input of the full-order observer, the rotor speed and disturbance torque are estimated. The proposed sensorless vector control scheme is demonstrated with experimental results     

Decoupled stator-flux-oriented induction motor drive with fuzzyneural network uncertainty observer

A stator-flux-oriented induction motor drive using online rotor time-constant estimation with a robust speed controller is introduced in this paper. The estimation of the rotor time constant is made on the basis of the model reference adaptive system using an energy function. The estimated rotor time-constant is used in the current-decoupled controller, which is designed to decouple the torque and flux in the stator-flux-field-oriented control. Moreover, a robust speed controller, which is comprised of an integral-proportional speed controller and a fuzzy neural network uncertainty observer, is designed to increase the robustness of the speed control loop. The effectiveness of the proposed control scheme is demonstrated by simulation and experimental results     

Sensorless Control of Induction Motors by Reduced Order Observer With MCA EXIN + Based Adaptive Speed Estimation

This paper presents a sensorless technique for high-performance induction machine drives based on neural networks. It proposes a reduced order speed observer where the speed is estimated with a new generalized least-squares technique based on the minor component analysis (MCA) EXIN + neuron. With this regard, the main original aspects of this work are the development of two original choices of the gain matrix of the observer, one of which guarantees the poles of the observer to be fixed on one point of the negative real semi-axis in spite of rotor speed, and the adoption of a completely new speed estimation law based on the MCA EXIN + neuron. The methodology has been verified experimentally on a rotor flux oriented vector controlled drive and has proven to work at very low operating speed at no-load and rated load (down to 3 rad/s corresponding to 28.6 rpm), to have good estimation accuracy both in speed transient and in steady-state and to work correctly at zero-speed, at no-load, and at medium loads. A comparison with the classic full-order adaptive observer under the same working conditions has proven that the proposed observer exhibits a better performance in terms of lowest working speed and zero-speed operation     

异步电机自适应矢量控制系统研究

提出了一种速度自适应的转子磁链闭环观测器,并应用于矢量控制系统中,以取代传统的纯积分器。经过理论证明,该系统是超稳定系统。针对1.1kW感应电机,采用MATLAB／SIMULINK仿真软件对系统进行仿真,仿真结果表明该方案对电机参数变化的鲁棒性较好,磁链观测精度高。同时,基于磁链状态观测器设计的速度辨识方案收敛速度快．精度高,尤其是在较低转速下仍能保持很高的精度。     

A novel sliding-mode observer for indirect position sensing ofswitched reluctance motor drives

A switched reluctance motor (SRM) drive generally requires a rotor position sensor for commutation and current control. However, the use of this position sensor increases both cost and size of the motor drive and causes limitations for industrial applications. In this paper, a novel indirect position sensing technique, namely, the sliding-mode observer, is proposed for SRM drives. The corresponding design approach and operating performance are provided to illustrate the fast convergence and high robustness of the observer against disturbances and variations     

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     

A state observer for the permanent-magnet synchronous motor

An identity state observer for the permanent-magnet synchronous motor is derived which reconstructs the electrical and mechanical states of the motor from current and voltage measurements. The observer operates in the rotor frame and estimates direct and quadrature stator currents, rotor velocity, and rotor position. Since the rotor position is estimated, the rotor reference frame is approximated using the latest rotor position estimate. The motor dynamics and the transformation into the estimated rotor frame are nonlinear, and thus the observer and observer error dynamics are nonlinear. Therefore, stability is analyzed using a linearized error model. Simulations including realistic measurement disturbances are used to investigate the global stability and accuracy of the observer     

一种基于空域和频域信息的固定单站无源定位跟踪改进算法

针对无源定位必须实现快速和稳定定位跟踪的要求,本文基于辐射源信号的空域和频域信息,提出了一种对运动辐射源的固定单站无源定位跟踪改进算法。文中首先利用辐射源信号的空域和频域变化量信息,通过伪线性卡尔曼滤波算法估计出目标的速度矢量;然后利用速度矢量的估计值直接获得目标位置矢量的估计,并将其作为标准卡尔曼滤波算法的观测值进行滤波;最后通过计算机仿真验证了该方法具有较高的定位精度和较快的收敛速度。     

Design and implementation of the extended Kalman filter for thespeed and rotor position estimation of brushless DC motor

A method for speed and rotor position estimation of a brushless DC motor (BLDCM) is presented in this paper. An extended Kalman filter (EKF) is employed to estimate the motor state variables by only using measurements of the stator fine voltages and currents. When applying the EKF, it was necessary to solve some specific problems related to the voltage and current waveforms of the BLDCM. During the estimation procedure, the voltage- and current-measuring signals are not filtered, which is otherwise usually done when applying similar methods. The voltage average value during the sampling interval is obtained by combining measurements and calculations, owing to the application of the predictive current controller which is based on the mathematical model of motor. Two variants of the estimation algorithm are considered: (1) speed and rotor position are estimated with constant motor parameters and (2) the stator resistance is estimated simultaneously with motor state variables. In order to verify the estimation results, the laboratory setup has been constructed using a motor with ratings of 1.5 kW, 2000 r/min, fed by an insulated gate bipolar transistor inverter. The speed and current controls, as well as the estimation algorithm, have been implemented by a digital signal processor (TMS320C50). The experimental results show that is possible to estimate the speed and rotor position of the BLDCM with sufficient accuracy in both steady-state and dynamic operation. Introducing the estimation of the stator resistance, the speed estimation accuracy is increased, particularly at low speeds. At the end of the paper, the characteristics of the sensorless drive are analyzed. A sensorless speed control system has been achieved with maximum steady-state error between reference and actual motor speed of ±1% at speeds above 5% of the rated value     

基于自适应状态观测器的异步电机无速度传感器矢量控制系统

异步电机无速度传感器矢量控制系统是目前研究的热点,本文采用一种闭环磁链观测器,即自适应状态观测器对转子磁链进行观测,与传统开环电压、电流模型相比,观测效果更好。在转子磁链观测的基础上,采用PI型自适应律,对转速进行了辨识。最后,通过Matlab仿真验证了本文给出的异步电机无速度传感器矢量控制系统的可行性,仿真结果表明该系统具有较好的动、静态性能,并具有一定的抗干扰能力。     

A new method of rotor resistance estimation for vector-controlledinduction machines

The estimation of rotor time constant, or rotor resistance, in a vector-controlled induction machine is necessary to achieve high-performance torque control. A new method of estimating the rotor resistance online, for use in a vector-controlled induction machine, is presented. It uses short duration pulses added to the constant flux reference current i_dse* and based on the resultant torque command current produced by a proportional-integral controller i_qse * adjusts the rotor resistance estimate. This method of self-tuning the vector controller to the rotor time constant, when operating in a closed-loop speed control loop, does not produce torque pulsations when correctly tuned. In comparison to other online methods such as the extended Kalman filter and the extended Luenberger observer, this method does not require voltage sensors and is computationally simpler. The rotor resistance estimation technique is illustrated through simulation and practical implementation of a vector-controlled induction machine