scholarly journals A novel FPGA‐Based Bi input‐reduced order extended Kalman filter for speed‐sensorless direct torque control of induction motor with constant switching frequency controller

2021 ◽  
Vol 15 (3) ◽  
pp. 185-201
Author(s):  
Remzi Inan
Author(s):  
Mohamed Chebaani ◽  
Amar Goléa ◽  
Med Toufik Benchouia ◽  
Noureddine Goléa

Purpose Direct Torque Control (DTC) of induction motor drives is a well-established technique owing to features such as fast dynamic and insensibility to motor parameters. However, conventional DTC scheme, based on comparators and the switching table, suffers from large torque and flux ripples. To improve DTC performance, this study aims to propose and implement a sensorless finite-state predictive torque control using extended Kalman Filter in dSPACE environment. Design/methodology/approach This paper deals with the design of an extended Kalman filter for estimating the state of an induction motor model and for sensorless control of systems using this type of motor as an actuator. A complex-valued model is adopted that simultaneously allows a simpler observability analysis of the system and a more effective state estimation. Findings Simulation and experimental results reveal that the drive system, associated with this technique, can effectively reduce flux and torque ripples with better dynamic and steady state performance. Further, the proposed approach maintains a constant switching frequency. Originality/value The proposed speed observer have been developed and implemented experimentally under different operating conditions such as parameter variation, no-load/load disturbances and speed variations in different speed operation regions.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Asghar Taheri ◽  
Hai-Peng Ren ◽  
Chun-Huan Song

In this paper, a simple extended Kalman Filter (EKF) controller for direct torque control (DTC) of a six-phase induction machine in all speed ranges is proposed. The aim of this paper is to decrease the execution time of EKF modeling of a six-phase induction motor. The proposed method is fast and can operate online. If the machine parameters are changed during the operation, the EKF algorithm is activated to find parameters used for controlling the motor. In low speed, not only the motor speed measurement but also the DTC of machine is difficult. The EKF model can estimate speed, flux, load torque, and stator resistance in low speed; thus, optimization can be performed in all loads and speed range. The proposed method increases the accuracy of DTC of the six-phase induction machine and decreases the computation cost of the system using the simplified algorithm. The simulation and experimental results verify the effectiveness and the robustness of the proposed method against parameter variations.


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