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.     

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     

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.     

Unified sensorless vector control of synchronous and induction motors

In this paper, a unified theory for sensorless flux estimation and vector control of induction motors and nonsalient permanent-magnet synchronous motors (PMSMs) is developed. It is shown that an estimator and vector controller for one of the motor types can also be applied to the other, with only minor modifications necessary. Two candidate estimators are considered: a variant of the well-known "voltage model" (VM) and a phase-locked-loop-type speed and position estimator. These are applied to both motor types, and evaluated experimentally. For the nonsalient PMSM, an important result is that synchronization can be guaranteed from any initial rotor position.     

Field-oriented control of induction motors using neural-networkdecouplers

This paper presents a novel approach to the field-oriented control (FOC) of induction motor drives. It discusses the introduction of artificial neural networks (ANNs) for decoupling control of induction motors using FOC principles. Two ANNs are presented for direct and indirect FOC applications. The first performs an estimation of the stator flux for direct field orientation, and the second is trained to map the nonlinear behavior of a rotor-flux decoupling controller. A decoupling controller and flux estimator were implemented upon these ANNs using the MATLAB/SIMULINK neural-network toolbox. The data for training are obtained from a computer simulation of the system and experimental measurements. The methodology used to train the networks with the backpropagation learning process is presented. Simulation results reveal some very interesting features and show that the networks have good potential for use as an alternative to the conventional field-oriented decoupling control of induction motors     

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     

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.     

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.     

Motion control with induction motors

Induction motors (IM) provide a very wide speed range, mechanically robust and relatively low cost motion control option. An up-to-date summary of the status of induction motor motion control technology is the subject of this paper. The topics which this paper includes are as follows: basic motion control system requirements; field orientation instantaneous torque control principles for induction motors (FO-IM); current regulators for induction motor motion control; flux and torque regulators for induction motor motion control; self commissioning and continuous self-tuning for field orientation. Technology advances based on modern control and estimation theory have the potential to further enhance the capability of this important class of servo drive systems     

A vector control scheme for EV induction motors with a series ironloss model

Electric vehicle (EV) motors are characterized by their low inductance and high current density, so that they run at high speed and produce a high starting torque. Due to the low inductance coil design, the current ripple caused by pulsewidth modulation (PWM) switching makes a significant amount of eddy-current loss and hysteresis loss, especially in high-speed operation. If one simply neglects the iron loss, the overall vector controller is detuned, resulting in an error in the torque control. The iron loss is modeled, in general, by a parallel resistor R_M to the magnetizing inductor L_M. The authors propose a series R-L model that accounts for the effects of the iron loss. A major advantage of the series model is that it does not increase the number of state variables in developing a vector control. In this paper, they derive a rotor-flux-oriented flux error, orientation angle error, and torque error caused by iron loss. Finally, they demonstrate the effectiveness of the proposed control method through computer simulation and experimental results     

Passivity-based control of saturated induction motors

A passivity-based controller, which takes into account saturation of the magnetic material in the main flux path of the induction motor, is developed to provide close tracking of time-varying speed and flux trajectories in the high magnetic saturation regions. The proposed passivity based controller is experimentally verified. Also, a comparison between the controllers based on the saturated and nonsaturated magnetics is presented to demonstrate the benefit of the controller based on the saturated magnetics     

Sensorless sliding-mode control of induction motors

This paper develops the ideas of speed- and flux-sensorless sliding-mode control for an induction motor illustrated in previous work by one of the authors. A sliding-mode observer/controller is proposed in this paper. The convergence of the nonlinear time-varying observer along with the asymptotic stability of the controller is analyzed. Pulsewidth modulation implementation using sliding-mode concepts is also discussed. Major attention is paid to torque control, and then the developed approach is utilized for speed control. Computer simulations and experiments have been carried out to test the proposed estimation and control algorithm. The experimental results demonstrated high efficiency of the proposed estimation and control method.     

New natural observer applied to speed-sensorless DC servo and induction motors

A simple observer design technique with parameter adaptation is proposed for bounded-input bounded-output nonlinear systems. In this technique, no feedback is used in the observer but parameter estimations are considered as if they are observer inputs. The proposed technique is successfully applied to speed-sensorless dc servomotors and speed-sensorless induction motors with load torque adaptation schemes. The observer is robust to noise and parameter uncertainty. Excellent experimental and simulation results have been obtained.     

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     

Robust control using neural network uncertainty observer for linearinduction motor servo drive

A robust controller, that combines the merits of integral-proportional (IP) position control and neural network (NN) observed technique, is designed for a linear induction motor (LIM) servo drive in this study. First, the secondary flux of the LIM is estimated using a sliding-mode flux observer on the stationary reference frame and the feedback linearization theory is used to decouple the thrust and the flux amplitude of the LIM. Then, the IP position controller is designed according to the estimated mover parameters to match the time-domain command tracking specifications. Moreover, a robust controller is formulated using the NN uncertainty observer, which is implemented to estimate the lumped uncertainty of the controlled plant, as an inner-loop force controller to increase the robustness of the LIM servo drive system. Furthermore, in the derivation of the online training algorithm of the NN, an error function is used in the Lyapunov function to avoid the real-time identification of the system Jacobian. In addition, to increase the speed and accuracy of the estimated flux, the sliding-mode flux observer is implemented using a 32 bit floating-point digital signal processor (DSP) with a high sampling rate. The effectiveness of the proposed control scheme is verified by both the simulated and experimental results     

Flux observer with online tuning of stator and rotor resistancesfor 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     

Minimum-time minimum-loss speed control of induction motors underfield-oriented control

A new minimum-time minimum-loss speed control algorithm for induction motors is suggested to obtain high performance, as well as high efficiency, under field-oriented control with practical constraints on voltage and current. This algorithm utilizes a two-stage control. In the transient stage, a maximum torque control algorithm is utilized to get the minimum-time response. In the steady state, a minimum-loss control algorithm is applied to improve the efficiency. Simulation studies show the performance of the proposed minimum-time minimum-loss control algorithm under field-oriented control     

Adaptive robust fast control for induction motors

A new induction motor position controller that exhibits fast response and robustness is proposed. The control strategy is based on the well-known linear quadratic regulator design principle. By adaptively adjusting a penalty parameter, it is shown that the control strategy enables the induction motor system to exhibit fast convergence. Meanwhile, since the sliding mode will occur in the transient process, the fast control inherits the robustness in matched uncertainties of the sliding-mode control. In addition, to alleviate the chattering effect of the switching control signal, a low-pass filter is used to smooth the control and its design is integrated with the switching control design. The performance of the proposed control strategy is verified by experimental results     

Sensorless control of induction motors by artificial neuralnetworks

In this letter, we propose a voltage-source inverter control working in the open loop of an induction motor measuring the stator current and using an artificial neural network. This technique has the mission to estimate the speed and torque of the rotor without using sensors. With this, a simple and cheap method of control is obtained, with as much precision and robustness as other more complex ones