scholarly journals Simulation and Implementation of Predictive Speed Controller and Position Observer for Sensorless Synchronous Reluctance Motors

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2712
Author(s):  
Tian-Hua Liu ◽  
Seerin Ahmad ◽  
Muhammad Syahril Mubarok ◽  
Jia-You Chen
Keyword(s):  
Digital Signal Processor ◽  
Digital Signal ◽  
Rotor Position ◽  
Speed Controller ◽  
Synchronous Reluctance Motor ◽  
Satisfactory Performance ◽  
Reluctance Motor ◽  
Predictive Controller ◽  
Drive Systems ◽  
Position Observer

A position observer and a predictive controller for sensorless synchronous-reluctance-motor (SynRM) drive systems are investigated in this paper. The rotor position observer, based on motor parameters, and stator currents and voltages, was designed and implemented to compute the rotor position. A pole-assignment technique was used to provide similar converging rates of the position observer, even when operated at different speeds. Furthermore, a predictive controller was designed to enhance performance. A digital-signal processor (DSP), TMS-320F-28335, was used as a computation tool. Several simulated results are provided and compared with the measured results. The measured results showed that the implemented predictive controller sensorless SynRM drive system could be adjusted from 30 to 1800 rpm with satisfactory performance, including quicker and better tracking responses, and a lower speed drop than that of a proportional-integral (PI) controller.

scholarly journals Design and Implementation of Position Sensorless Field-Excited Flux-Switching Motor Drive Systems

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3672
Author(s):  
Tian-Hua Liu ◽  
Muhammad Syahril Mubarok ◽  
Yu-Hao Xu
Keyword(s):  
Digital Signal Processor ◽  
Position Estimation ◽  
Drive System ◽  
Dynamic Responses ◽  
Motor Drive ◽  
Rotor Position ◽  
Speed Controller ◽  
Drive Systems ◽  
Predictive Controllers ◽  
Flux Switching Motor

Field-excited flux-switching motor drive systems have become more and more popular due to their robustness and lack of need for a permanent magnet. Three different types of predictive controllers, including a single-step predictive speed controller, a multi-step predictive speed controller, and a predictive current controller are proposed for sensorless flux-switching motor drive systems in this paper. By using a 1 kHz high-frequency sinusoidal voltage injected into the field winding and by measuring the a-b-c armature currents in the stator, an estimated rotor position that is near ± 2 electrical degrees is developed. To improve the dynamic responses of the field-excited flux-switching motor drive system, predictive controllers are employed. Experimental results demonstrate the proposed predictive controllers have better performance than PI controllers, including transient, load disturbance, and tracking responses. In addition, the adjustable speed range of the proposed drive system is from 4 r/min to 1500 r/min. A digital signal processor, TMS-320F-2808, is used as a control center to carry out the rotor position estimation and the predictive control algorithms. Measured results can validate the theoretical analysis to illustrate the practicability and correctness of the proposed method.

Sensorless Control of IPMSM Using Modified Current Slope Estimation Method

2012 ◽  
Vol 150 ◽  
pp. 100-104
Author(s):  
Tao Zhang ◽  
Wei Ni ◽  
Hui Ping Zhang ◽  
Sha Sha Wu
Keyword(s):  
Permanent Magnet ◽  
Digital Signal Processor ◽  
Permanent Magnet Synchronous Motor ◽  
Estimation Method ◽  
Digital Signal ◽  
Synchronous Motor ◽  
Low Speed ◽  
Rotor Position ◽  
Operating Region ◽  
Interior Permanent Magnet

When the permanent magnet synchronous motor is operated at a low speed. The rotor position and speed are very difficult to estimate using the extended flux or back EMF method. A novel modified current slope estimating method is used to estimate the rotor position and speed in low speed in this paper. The mathematical models of an interior permanent magnet synchronous motor (IPMSM) are deduced. The basic principle of modified current slope method is introduced. The simulation control system is built based on Matlab and a TMS320LF2407 digital signal processor is used to execute the rotor position and speed estimation. The experimental and simulation results have shown that the rotor position and speed can be accurately estimated in a low-speed operating region.

scholarly journals Simplified Sensorless Current Predictive Control of Synchronous Reluctance Motor Using Online Parameter Estimation

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 492 ◽  
Author(s):  
Ahmed Farhan ◽  
Mohamed Abdelrahem ◽  
Amr Saleh ◽  
Adel Shaltout ◽  
Ralph Kennel
Keyword(s):  
Parameter Estimation ◽  
Predictive Control ◽  
Operating Conditions ◽  
Parameter Mismatch ◽  
Speed Controller ◽  
Synchronous Reluctance Motor ◽  
Reluctance Motor ◽  
Finite Set ◽  
Insufficient Response ◽  
The Cost

In this paper, a simplified efficient method for sensorless finite set current predictive control (FSCPC) for synchronous reluctance motor (SynRM) based on extended Kalman filter (EKF) is proposed. The proposed FSCPC is based on reducing the computation burden of the conventional FSCPC by using the commanded reference currents to directly calculate the reference voltage vector (RVV). Therefore, the cost function is calculated for only three times and the necessity to test all possible voltage vectors will be avoided. For sensorless control, EKF is composed to estimate the position and speed of the rotor. Whereas the performance of the proposed FSCPC essentially necessitates the full knowledge of SynRM parameters and provides an insufficient response under the parameter mismatch between the controller and the motor, online parameter estimation based on EKF is combined in the proposed control strategy to estimate all parameters of the machine. Furthermore, for simplicity, the parameters of PI speed controller and initial values of EKF covariance matrices are tuned offline using Particle Swarm Optimization (PSO). To demonstrate the feasibility of the proposed control, it is implemented in MATLAB/Simulink and tested under different operating conditions. Simulation results show high robustness and reliability of the proposed drive.

Computer aided models for the characterization of synchronous reluctance motor drive systems

1999 ◽  
Vol 14 (4) ◽  
pp. 1459-1464 ◽  
Author(s):  
A.A. Arkadan ◽  
F.N. Isaac ◽  
A.A. Russell ◽  
A. El-Antably ◽  
N.A. Demerdash
Keyword(s):  
Motor Drive ◽  
Synchronous Reluctance Motor ◽  
Reluctance Motor ◽  
Computer Aided ◽  
Drive Systems

scholarly journals A Dual-Voltage-Vector Model-Free Predictive Current Controller for Synchronous Reluctance Motor Drive Systems

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1743 ◽  
Author(s):  
Cheng-Kai Lin ◽  
Jen-te Yu ◽  
Hao-Qun Huang ◽  
Jyun-Ting Wang ◽  
Hsing-Cheng Yu ◽  
...  
Keyword(s):  
Vector Model ◽  
Motor Drive ◽  
Model Free ◽  
Synchronous Reluctance Motor ◽  
Voltage Vector ◽  
Current Controller ◽  
Reluctance Motor ◽  
Drive Systems

Rotor Position Error Compensation in Sensorless Synchronous Reluctance Motor Drives

2021 ◽  
pp. 1-1
Author(s):  
Salvatore Foti ◽  
Luigi Tornello ◽  
Antonio Testa ◽  
Giacomo Scelba ◽  
Salvatore De Caro ◽  
...  
Keyword(s):  
Error Compensation ◽  
Motor Drives ◽  
Position Error ◽  
Rotor Position ◽  
Synchronous Reluctance Motor ◽  
Reluctance Motor
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