Improved Sliding-Mode Observer for sensorless control of five-phase induction motor

This paper presents the use of a higher order sliding mode scheme for sensorless control of induction motors. The second order sub-optimal control law is based on a reduced-order model of the motor, and produces the references for a current regulated PWM inverter. A nonlinear observer structure, based on Lyapunov theory and on different sliding mode techniques (first order, sub-optimal and super-twisting) generates the velocity and rotor flux estimates necessary for the controller, based only on the measurements of phase voltages and currents. The proposed control scheme and observers are tested on an experimental setup, showing a satisfactory performance.

This project investigates the application of model reference adaptive system (MRAS) for the speed sensorless control of an induction motor. The rotor speed can be accurately estimated by employing the closed-loop observer named reactive MRAS. Therefore, this observer eliminates the need of a speed sensor for the control of the motor speed. The method is robust to stator and rotor resistance variations due to change of temperature. The dynamic system equations of the induction machines are formulated, and the motor control system performance is studied. Both scalar voltage-to-frequency (V/f) control and vector field oriented control (FOC) schemes, implemented using digital signal processor (DSP), are investigated. The design of the speed sensorless DSP-based controller is completed. Software packages have been developed to implement the design. An experimental system using the proposed controller has been built. Various tests have been conducted to verify the technical feasibility of the control technique. The experimental results confirm the feasibility of the proposed speed sensorless V/f control scheme using MRAS speed estimator. The designed V/f profile has been tested. Even with step change of the load or that of the command speed, the system can achieve the correct steady state after a short transient operation. The experimental results also confirm the feasibility of the proposed speed sensorless FOC control scheme using MRAS speed estimator. The current regulators meet the design requirements. Both the flux-producing current component and the torque-producing current component can be controlled separately. In the implementation, digital signal processor (DSP) TMS320 FL2407 and voltage source inverter (VSI) Skiip 342GD120-316CTV are employed. The modular strategy is adopted to develop the software package.

Predictive torque control (PTC) is an emerging and promising technology in electric drives. The effective performance of the PTC drive lies in its simple control law wherein different constraints can be easily added with weighting factors. However only empirical approximation methods are used for the determination of weighting factor. This paper presents a ranking weight method to find the weighting factor in predictive torque control of five-phase induction motor (IM). The weighting factor value is based on the rank ordering of the criteria (such as torque, flux, xy-plane current harmonics, CMV etc.) considered in the cost function. Assigning weights based on the rank of the criteria is more reliable than randomly assigning weights to the criteria because the decision makers are more confident on the ranks of the criteria than weights. Rank order centroid (ROC) weight technique is presented and compared with conventional weighting technique. The viability of the concept is verified by numerical simulations and the results are validated through experimentation.

The mathematical model of the five-phase squirrel-cage induction motor and the system of the dual five-phase voltage source inverter have been presented. The control methods and control systems of the field-oriented control of the five-phase induction motor with an open-end stator winding are described. The structures of the direct fieldoriented control system (DFOC) and the Indirect Field-oriented control system (IFOC) with PI controllers in outer and inner control loops are analyzed. A method of space vector modulation used to control the system of the dual five-phase voltage source inverter has been discussed. The results of simulation studies of the field-oriented control methods are presented. Comparative analysis of the simulation results was carried out.

Energy optimized sliding-mode control of sensorless induction motor drives

This paper presents a sensorless speed control method of permanent magnet synchronous motor (PMSM) applying sliding-mode control theory, to enhance the observation precision and improve robustness of control system. Firstly, an improved full-order sliding mode observer (FSMO) with sigmoid function is gifted to weaken the high-frequency (HF) chattering caused by conventional sliding mode observer (SMO). The quadrature phase-locked loop (PLL) is used to calculate high-precision rotor location and speed, avoiding the use of filter. Then the nonsingular fast terminal sliding mode controller (NFTSMC) in speed controller is introduced to replace traditional proportional integral (PI) controller to improve the dynamic performance of control system. The outcomes verify that the presented control method enhances the overall observation precision, suppresses HF chattering, and increases dynamic and stable state response of PMSM.

Based on the application of sensorless control for permanent magnet synchronous motors(PMSM), this paper put forward an improved sliding mode observer(SMO). The conventional SMOs use discontinuous step sign functions as switching functions, which cause chattering problems in the estimation of back electromotive force. Therefore, a smooth activation function is adopted as the switching function. An adaptive reaching law is devised to enhance stability of observing. To address the delay of phase issue caused by low-pass filters(LPF), an adaptive cut-off frequency is designed. The speed and angle information are estimated by using a phase-locked loop(PLL) in the place of of the arctan function, and phase compensation is implemented. Finally, the system of controlling motor is simulated in Matlab to verify that the sensorless control method according to the improved SMO has the effect of reducing chattering and improving the control accuracy of the system.

Real time implementation of indirect rotor flux oriented control of a five-phase induction motor with novel rotor resistance adaption using sliding mode observer

This paper proposes an improved Sliding Mode Observer (SMO). Compared with the traditional SMO, it can estimate position and speed information of the rotor more accurately. Its stability is proved by Lyapunov Stability. A control scheme of Permanent Magnet Synchronous Motor (PMSM) under Direct Torque Control (DTC) is designed, using the improved SMO as the feedback of speed information. The results show that the proposed method works well without position encoder. The improved SMO guarantees DTC scheme quick response and strong robustness.

This work deals with a sensorless speed control for three-phase induction motor in order to improve its operation at low speed. Initially, a direct field oriented control employing space vector pulse with modulation based on sliding mode observer (SMO) is studied and evaluated due to its high accuracy in estimating the flux at low speed. The proposed current model based on SMO provides good speed estimation under low speed and parameter or load changes. Simulations and experimental tests with diferent operational conditions at low speed are carried out in order to test the sensorless control. The results show a good perfomance and agreed with the results shown in recent papers.

Speed and torque control of an induction motor is usually attained by application of a speed or position sensor. However, speed and position sensors require the additional mounting space, reduce the reliability in harsh environments and increase the cost of the motor. Various control algorithms have been proposed for the elimination of speed and position sensors. This paper investigates a novel speed sensorless control of an induction motor. The proposed control strategy is based on MRAS (model reference adaptive system) using state observer model with current error feedback and rotor current model as two models for flux estimation. The rotor speed is estimated so that the difference between the outputs of state observer model and rotor current model may be zero. This algorithm may overcome several shortages of conventional MRAS: integrator problems, small EMF at low speed, and relatively large sensitivity to resistance variation. The proposed algorithm is verified through simulation and experiment.

Induction motor is a cast of alternating current motor where charge endures allotted to the rotor close-at-hand deputation of conductive charge. These motors are broadly applied in industrial claim due to they are arduous along with adhere no contacts. The speed controller of deltoid phase induction motor is applied to alleviate the aberration of speed. The central constructivist of this paper is to accrue the performance of speed sensorless control of three phase induction motor. To increase its performance, this paper presents a modified method for speed controller of an indirect vector-controlled induction motor drive using cloud computing technique. Our methodology depends on speed sensorless scheme to obtain the speed signal feedback; the speed estimator is based on model reference adaptive control that uses the stator current and rotor flux as state variables for estimating the speed. In this method, the stator current error is represented as a function of first degree of the estimated speed error. An analysis and simulation of the tried algorithm is birthed and applied easing a TMS320C31 floating-point notational alert Processor. And accumulate the action of the three phase induction motor we conceived our appraisals affixed to the accountant based on cloud computing tactics. This intelligent policy uses the guidelines of the speed controller efficiently. Simulation and experimental results depicted that the motor speed is decelerated articulately to destine its illusion apprise without above and inferior smack and with about zero steady state error. The apprised accelerate alert and its dispatching buoy amassed off line from burlesque. After effects display an advantageous affinity among the accounted speed alert and it's dispatching allocated as well as aped speed flares.

Model reference adaptive system (MRAS) based techniques are one of the best methods to estimate the rotor speed. Speed and torque control of an induction motor is usually attained by application of a speed or position sensor. However, these require the additional mounting space, reduce the reliability and increase the cost of the motor. The recent trend in field oriented control (FOC) is towards the use of sensorless techniques that avert the use of speed sensor and flux sensor. This paper seeks to provide a direct comparison between two technics of induction motor MRAS based speed estimators, one based on the rotor flux and the other based on the back EMF. Comparison between the two techniques is made through computer simulations.

This research paper presents a novel method for the speed control of induction motors without using a speed sensor. The rotor speed can be accurately computed using an optimal control observer named the Kalman filter designed in this research paper. This replaces a speed sensor and eliminates the difficulty of the sensor installation in many applications. This research paper presents an advanced field oriented control of induction motors, based on a specific d-q coordinate model with the d-coordinate chosen to be in line with the rotor flux and the q-coordinate chosen to be 90⁰ lagging. The position of the rotor flux can be accurately computed using the Kalman filter. This eliminates the position sensors required accurately to monitor the flux. This research paper shows that as a result of this specific d-q transformation, the motor torque is proportional to the product of the rotor flux and the q-coordinate stator current. This significantly simplifies the induction motor control, such that the rotor flux is simply controlled by regulating the flux-related d-coordinates stator current and the motor torque is controlled just by regulating the q-coordinate stator current. This research paper presents a computational efficient recursive algorithm for Kalman filter which is specifically designed for the induction motor control. The Kalman filter provides the minimum variance state estimation and tolerates induction motor modelling and measurement errors. The Kalman filter can process all available measurements regardless of their precision (only two input current measurements required for the motor control), and provides a quick and optimal estimate of the variables of interest (the rotor speed and flux selected as outputs), as well as achieves a fast convergence. This research paper presents the digital signal processor (DSP) implementation of the field oriented control of induction motors using Kalman filter. The hardware requirements and all software modules are detailed. The experimental verification of the control method designed in this research paper is provided. Typical measurements are given to demonstrate the efficiency of the novel control presented in this research paper.

In sensorless control, sliding mode observer is widely used because of its insensitivity to parameter changes and strong robustness. For unnecessary high frequency chattering and the lack of accuracy in calculation of rotor position and machine speed in the conventional sliding mode observer, a new sliding mode observer based on the new constant velocity reaching law is used to suppress the high frequency chattering of the machine system. A new constant speed reaching law is designed to replace the conventional constant speed reaching law and it is introduced into new sliding mode observer. This method improves the approaching speed of sliding mode and reduces the high frequency chattering of conventional sliding mode observer. In addition, the arctangent function is used to estimate the position of the machine rotor, and the phase compensation for the Angle position error of the machine rotor is carried out. The simulation results show that compared with the Conventional sliding mode observer, the proposed new sliding mode observer is more stable and has better control performance.