Yahya Ahmed Alamri

Using NSGA II multiobjective genetic algorithm for EKF-based estimation of speed and electrical torque in AC induction machines

High-performance AC drives require accurate speed and torque estimations to provide a proper system operation. The selection and quality of extended Kaiman fitter (EKF) covariance elements have a considerable bearing on the effectiveness of motor drive. Many EKF-based optimization techniques involve only a single objective for the optimal estimation of speed without giving concern to the torque. This paper presents a new methodology for the selection of EKF filters that uses non-dominated sorting genetic algorithm-II (NSGA-II) developed for filter element selection in order to investigate the concurrent optimization of speed and torque. The proposed optimizing technique for EKF-based estimation scheme is used in the combination with the sensorless direct torque control of induction motor. The multi-optimal based-EKF is tested with three regions of Pareto front curve.

Improved EKF-based direct torque control at the start-up using constant switching frequency

A sensorless extended Kalman filter (EKF) based direct torque control (DTC) with the use of a constant switching frequency control (CSFC) of induction machine is proposed in this research work. This paper is meant to investigate the dynamic performance for DTC-CSFC and DTC with a hysteresis torque controller by applying different speed step changes from three different low speed operations. The dynamic performance results show that the sensorless EKF-based DTC-CSFC is superior to the conventional EKF-based DTC when reference speed change is applied from 0 to 59 rad/s. Additionally, improvement in the reduction of torque ripples is achieved for all step changes of speed. The effectiveness of the proposed EKF-based DTC-CSFC is confirmed by experimental validation.

A simple approach for designing a PID controller for an experimental air blower system

This paper focuses on the identification and control of an air blower system PT-326. Modelling of the PT-326 system is required before designing the controller. Hence, it is estimated by using system identification toolbox available in MATLAB. The process of identification began with the collection of input and output data from an experiment. The collected data is used for model estimation based on the selection of auto-regressive with exogenous ARX model structure of the PT-326 system. Based on the input and output data of the system, best fit criterion and correlation analysis of the residual are analysed to determine the adequate parameters of ARX model representing the PT-326 system. To achieve a good performance for the air blower system, right selection of the PID controller parameters is essential. This paper also presents a simple approach for designing a PID controller using minimum square error tuning scheme and compares it with a conventional Ziegler-tuning method for the identified model via simulation and experiment. The results obtained from both tuning methods show that the outputs of the system with the PID controller in simulation and experiment are almost similar.

Sliding mode observer-based MRAS for direct torque control of induction motor

This paper proposes a sensorless sliding mode observer based model reference adaptive system applied to a direct torque control of the induction motor drive. The reference model is a sensorless sliding mode observer and the adaptive model is a typical current model. The proposed scheme provides speed and rotor flux estimations with the derivative of rotor flux set as the state of the adaptive mechanism. The simulation results show the effectiveness of the proposed observer compared with the conventional model reference adaptive system.

An improved flux regulation using a controlled hysteresis toque band for DTC of induction machines

This paper presents a dynamic hysteresis toque band strategy for improving flux regulation at low and zero speeds in a direct torque control (DTC)-look-up-table-based induction machine. The hysteresis torque band is controlled based on speed variation to solve the stator flux magnitude droops which normally occur at low frequency. The main benefit of the proposed approach is its simplicity, since it only requires a minor modification to the hysteresis band value and does not require an alteration on the lookup table. The simulation results of the proposed system showed a significant enhancement in speed and torque estimations at very low and zero speed and at the same time removes the problem of flux droop in the conventional hysteresis based DTC.