Comparative Analysis of Control Methods with Model Reference Adaptive System Estimators of a Seven-Phase Induction Motor with Encoder Failure

Abstract

This article presents a comparative analysis of the direct torque control with space vector modulation method for seven-phase squirrel-cage induction motor during the encoder failure. The direct torque control with space vector modulation method with model reference adaptive system with current model and current estimator and model reference adaptive system—flux based estimator applied in the control loop of the motor speed have been analyzed. The mathematical model of the seven-phase induction motor and model reference adaptive system-type estimators have been described. The method of space vector modulation applied to the seven-phase voltage source inverter, controlled seven-phase induction motor, has been described. The operation of direct torque control with space vector modulation has been verified via simulation tests, and the results of performed simulation studies have been analyzed and presented. The authors’ original contribution and work novelty includes comparison studies of the performance of the direct torque control method with space vector modulation of a seven-phase induction motor with two estimators: model reference adaptive system—flux based estimator and the novel model reference adaptive system with current model and current estimator.

Ripple Attenuation for Induction Motor Finite Control Set Model Predictive Torque Control Using Novel Fuzzy Adaptive Techniques

“…When designing a membership function, the following aspects need to be considered. (1) The membership functions have to fully cover the fuzzy domain. Otherwise, the blank area occurs, causing ineffective control.…”

“…Induction motors (IM) that are endowed with the advantages of simple and robust structure, low cost, stable operations and a wide speed regulation range have been broadly adopted in industrial applications, such as electric vehicles, mining and textile, etc. [1][2][3][4]. To ensure or improve the machine control performance, many advanced control strategies have been developed so far, the most famous being field-oriented control (FOC), which is based on the coordinate transformation principle [5][6][7].…”

“…Whereas, there are many reasons that can cause high speed, torque or flux ripples in the practical applications, and these can be grouped into internal and external factors [17][18][19][20][21][22][23][24][25]. The internal factors mainly include; (1) the values of the parameters (e.g., stator inductance and resistance, etc.) used for predictions are not consistent with the real ones [17];…”

Compensation of Torque-Producing Stator Current Error for Vector-Controlled Induction Motor Drives

“…Sensorless drives, sensor fault tolerant control and applications of artificial intelligence belong to the top topics in the field of sophisticated control methods for electrical controlled drives. In these cases, the vector control algorithm is mostly used as a basic control method [9][10][11][12][13][14][15]. This is the reason why it is important to suppress the aforementioned current control steady-state error, to reach the best possible performance of the drive.…”

Self-Tuning Observer for Sensor Fault-Tolerant Control of Induction Motor Drive

“…The disadvantage of most MRAS-type observers is the influence of the motor parameters (mainly the stator and rotor resistance) on the quality of the estimated quantities, especially at low speeds [26][27][28][29][30][31][32][33]. The proposed approach is independent of the motor parameters using a recursive least square method (RLS) to estimate the parameters of the speed and current observers.…”