Tze-Fun Chan

Speed estimation of an induction motor drive using an optimized extended Kalman filter

This paper presents a novel method to achieve good performance of an extended Kalman filter (EKF) for speed estimation of an induction motor drive. A real-coded genetic algorithm (GA) is used to optimize the noise covariance and weight matrices of the EKF, thereby ensuring filter stability and accuracy in speed estimation. Simulation studies on a constant V/Hz controller and a field-oriented controller (FOC) under various operating conditions demonstrate the efficacy of the proposed method. The experimental system consists of a prototype digital-signal-processor-based FOC induction motor drive with hardware facilities for acquiring the speed, voltage, and current signals to a PC. Experiments comprising offline GA training and verification phases are presented to validate the performance of the optimized EKF.

Modelling and Simulation of the Three-Phase Induction Motor Using Simulink

This paper describes a generalized model of the three-phase induction motor and its computer simulation using MATLAB/SIMULINK. Constructional details of various sub-models for the induction motor are given and their implementation in SIMULINK is outlined. Direct-online starting of a 7.5-kW induction motor is studied using the simulation model developed.

Modelling of the three-phase induction motor using SIMULINK

This paper describes a generalized simulation model of the three-phase induction motor using the SIMULINK software package of MATLAB. The model is based on two-axis theory of revolving frame transformation. The model takes power source and load torque as inputs and gives speed and electromagnetic torque as outputs. Internal resistance of the power supply and magnetic saturation of the motor may also be accounted for.

Application of Unscented Kalman filter to sensorless permanent-magnet synchronous motor drive

This paper studies the application of the Unscented Kalman filter (UKF) for a sensorless permanent-magnet synchronous motor (PMSM) drive. The principle of the UKF is reviewed and its adaptation to the PMSM model in the rotor reference frame is explained. For evaluation of drive performance a comparison with the classical Extended Kalman filter (EKF) based estimation method is made. The simulation results indicate that the UKF in general gives more accurate tracking of the rotor position than the EKF for constant torque operation. Besides, the UKF drive retains control over a longer standstill period. With the UKF-based sensorless PMSM drive, however, the proportional gain of the speed controller needs to be carefully chosen to avoid rotor hunting subsequent to step load changes.

A Comparative Study of Kalman Filtering for Sensorless Control of a Permanent-Magnet Synchronous Motor Drive

This paper presents a comparative study of the novel unscented Kalman filter (UKF) and the extended Kalman filter (EKF) for estimation of the rotor speed and position of a permanent-magnet synchronous motor (PMSM) drive. The general structure of the EKF and the UKF are reviewed. The various system vectors, matrices, models and algorithm programs are presented. Simulation studies on the two Kalman filters are carried out using Matlab and Simulink to explore the usability of the UKF in a sensorless PMSM drive. In order to compare the estimation performances of the observers, both filters are designed for the same motor model and control system and run with the same covariances. The simulation results indicate that the UKF is capable of tracking the actual rotor speed and position provided that the elements of the covariance matrices are properly selected. Since covariance tuning of the Kalman filter is often a trial-and-error process, an unconventional, asymmetric way of setting the model covariance parameters is introduced. It is shown that tuning is easier and the method gives a significant improvement in performance and filter stability

Permanent-Magnet Synchronous Generator Supplying an Isolated Load

The steady-state and transient performance of a surface-inset permanent-magnet synchronous generator (PMSG) feeding an isolated load is studied using a coupled-circuit, time-stepping, two-dimensional finite-element analysis. Nonlinearities in the field and electric circuit are taken into consideration and both passive ac load and bridge rectifier dc load operating conditions are analyzed. The main contribution of this paper is the quantitative analysis of voltage and current harmonics, as well as the study of short-circuit performance. The computed results have been verified by experiments on a 2.5 kVA generator.

Direct self control of induction motor based on neural network

This paper presents an artificial neural network (ANN) of direct self control (DSC) for induction motor to decrease the time consumption of conventional DSC controller. To cope with the complex calculation of DSC, the design employs the individual training strategy with the fixed-weight and the supervised models. The simulation results of ANN DSC system have demonstrated that ANN is available to implement the DSC theory for an induction motor.

A novel hybrid fuzzy/PI two-stage controller for an induction motor drive

In this paper, a novel hybrid fuzzy/PI controller for an induction motor drive is proposed. The major features of field-oriented control are exploited in the design of the scalar controller. A fuzzy logic slip-frequency controller operates together with a proportional-integral (PI) current controller to yield the desired values of slip-frequency and stator current during the acceleration/deceleration stage and the final steady-state stage. Detailed formulation of the fuzzy sets, the rule base, and the fuzzy inference of the slip frequency controller are presented. Simulation studies on a 150 W induction motor using Matlab/Simulink and hardware implementation based on an ADMC331 DSP board are performed. The simulation and experimental results indicate that the performance of the two-stage controller is comparable with that obtained using field-oriented control.

Computation of air-gap field in an axial-flux permanent-magnet machine using the method of images

The air gap field of a single-sided, axial-flux permanent-magnet machine (AFPMM) without armature core is computed using the concepts of magnetic charge and the method of images. The method is computationally efficient and yields results that cannot be obtained from the method based on the two-dimensional solution of Laplaces equation. The computed results have been verified by field measurements on an experimental machine.

Hybrid fuzzy two-stage controller for an induction motor

This paper presents a hybrid fuzzy/PI control scheme for an induction motor to overcome the drawback of the classical field-oriented control method. Using a two-stage (acceleration/deceleration stage and steady-state stage) strategy, the two features (frequency and current) of the field orientation principle are employed to design a scalar controller. The controller has the advantages of simplicity and insensitivity to motor parameter changes. The simulation results are very satisfactory.