Application of PSO Algorithm in PMSM Sensorless Control System

2013 ◽  
Vol 328 ◽  
pp. 123-127
Author(s):  
Tian Pei Zhou
Keyword(s):  
Control System ◽  
Sensorless Control ◽  
Fitness Function ◽  
Pso Algorithm ◽  
Speed Estimation ◽  
Motor Speed ◽  
Noise Parameter ◽  
Absolute Value ◽  
Time Integral ◽  
Matrix Parameter

Aiming at difficulty of determining the noise matrix parameter, PSO algorithm is applied to the optimization of noise parameter matrix. the fitness function is the time integral of the absolute value of the deviation between actual value and estimated value of the motor speed, the position of the particle, which makes the value of fitness function the smallest, is ultimately determined through constantly adjusting the position of the particle in the space, thereby computing matrix with the smallest deviation. The results show that the precision of speed estimation is obviously improved after noise matrix parameters of the system are optimized by PSO algorithm. And optimized waveform pulse of the motor speed is diminishes, speed-governing is more stable.

Speed Sensorless Control System Based on MRAS

2015 ◽  
Vol 742 ◽  
pp. 586-589
Author(s):  
Zhi Jiao
Keyword(s):  
Control System ◽  
Sensorless Control ◽  
Speed Estimation ◽  
Rotor Speed ◽  
Speed Sensorless ◽  
Motor Control System ◽  
Estimation Precision ◽  
Identification Theory ◽  
Stator Resistance ◽  
Model Reference Adaptive

In this paper, a strategy for estimating the induction motor’s rotor speed is proposed. The proposed rotor speed estimation strategy is based on model reference adaptive identification theory. By applying the proposed strategy, the induction motor control system can estimate the induction motor's rotor speed precisely. To improve the rotor speed estimation performance of the system, two methods have been adopt. The speed sensorless control system based on proposed strategy was built with Simulink blocks in Matlab platform. The corresponding simulation results demonstrate that the proposed method can operate stably in the whole range of speed with preferable estimation precision of stator resistance and rotor speed.

Optimization of PMSM Sensorless Control Based on Improved PSO Algorithm

2011 ◽  
Vol 383-390 ◽  
pp. 86-92
Author(s):  
Miao Wang Qian ◽  
Guo Jun Tan ◽  
Ning Ning Li ◽  
Zhong Xiang Zhao
Keyword(s):  
Particle Swarm Optimization ◽  
Simulated Annealing Algorithm ◽  
Sensorless Control ◽  
Fitness Function ◽  
Permanent Magnet Synchronous Motor ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Extend Kalman Filter ◽  
Swarm Optimization ◽  
Manual Adjustment

For the problem that manual adjustment of the parameters of controller in sensorless control system costs too much time, manpower and always can not get a good result, a new method based on improved particle swarm optimization algorithm is proposed to optimize the parameters. The improved algorithm is based on the standard particle swarm optimization with the simulated annealing algorithm and chaotic search brought in. The speed of motor is estimated by the extend Kalman filter. The error between measured speed and estimated speed of the permanent magnet synchronous motor rotor is used as the fitness function in order that the parameters in the covariance matrix is adjusted.The result of simulation indicates that high estimation precision can be got and the motor represents steadily with few of ripple of the actual speed.With this method, the time of adjustment is reduced and manpower is saved. In addition, the validity of the method is proved in experiment with dSPACE.

Design and Simulation of Speed Sensorless Control System for Induction Motor

2012 ◽  
Vol 201-202 ◽  
pp. 396-399
Author(s):  
Hong Yu Wang ◽  
Yan Peng ◽  
Yan Hou
Keyword(s):  
Control System ◽  
Induction Motor ◽  
Sensorless Control ◽  
Estimation Method ◽  
Estimation Accuracy ◽  
Speed Estimation ◽  
Rotor Speed ◽  
Speed Sensorless ◽  
Input Filter ◽  
Output Filter

In this paper, a method for estimating induction motor’s rotor speed is proposed. The proposed rotor speed estimation method is based on model reference adaptive identification theory. By applying the proposed method, the induction motor control system can estimate the rotor speed of the induction motor precisely. To improve the rotor speed estimation performance of the system, one input filter and one output filter are introduced into the speed sensorless control system. The introduced input filter and output filter enhance the estimation accuracy and improve the reliability and robustness of the system. The speed sensorless control system based on proposed method was built with Simulink blocks in Matlab platform. The simulation results indicate that the proposed method can operate stably in whole range of speed with preferable identification precision of the rotor speed.

scholarly journals Dead-Time Correction Applied for Extended Flux-Based Sensorless Control of Assisted PMSMs in Electric Vehicles

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 220
Author(s):  
Cheng Lin ◽  
Jilei Xing ◽  
Xingming Zhuang
Keyword(s):  
Control System ◽  
Electric Vehicles ◽  
Dead Time ◽  
Sensorless Control ◽  
Correction Method ◽  
Time Effect ◽  
Dead Time Correction ◽  
Speed Range ◽  
Time Correction ◽  
The Dead

Sensorless control technology of PMSMs is of great importance for safety and reliability in electric vehicles. Among all existing methods, only the extended flux-based method has great performance over all speed range. However, the accuracy and reliability of the extended flux rotor position observer are greatly affected by the dead-time effect. In this paper, the extended flux-based observer is adopted to develop a sensorless control system. The influence of dead-time effect on the observer is analyzed and a dead-time correction method is specially designed to guarantee the reliability of the whole control system. A comparison of estimation precision among the extended flux-based method, the electromotive force (EMF)-based method and the high frequency signal injection method is given by simulations. The performance of the proposed sensorless control system is verified by experiments. The experimental results show that the proposed extended flux-based sensorless control system with dead-time correction has satisfactory performance over full speed range in both loaded and non-loaded situations. The estimation error of rotor speed is within 4% in all working conditions. The dead-time correction method improves the reliability of the control system effectively.

scholarly journals Research on an Improved Sliding Mode Sensorless Six-Phase PMSM Control Strategy Based on ESO

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1292
Author(s):  
Hanying Gao ◽  
Guoqiang Zhang ◽  
Wenxue Wang ◽  
Xuechen Liu
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Sliding Mode ◽  
High Reliability ◽  
Permanent Magnet Synchronous Motor ◽  
Torque Ripple ◽  
Estimation Accuracy ◽  
Switching Function ◽  
Motor Speed ◽  
Rotor Position

The six-phase motor control system has low torque ripple, low harmonic content, and high reliability; therefore, it is suitable for electric vehicles, aerospace, and other applications requiring high power output and reliability. This study presents a superior sensorless control system for a six-phase permanent magnet synchronous motor (PMSM). The mathematical model of a PMSM in a stationary coordinate system is presented. The information of motor speed and position is obtained by using a sliding mode observer (SMO). As torque ripple and harmonic components affect the back electromotive force (BEMF) estimated value through the traditional SMO, the function of the frequency-variable tracker of the stator current (FVTSC) is used instead of the traditional switching function. By improving the SMO method, the BEMF is estimated independently, and its precision is maintained under startup or variable-speed states. In order to improve the estimation accuracy and resistance ability of the observer, the rotor position error was taken as the disturbance term, and the third-order extended state observer (ESO) was constructed to estimate the rotational speed and rotor position through the motor mechanical motion equation. Finally, the effectiveness of the method is verified by simulation and experiment results. The proposed control strategy can effectively improve the dynamic and static performance of PMSM.

The Research on Software of the Temperature Control of Motor Speed System

2010 ◽  
Vol 29-32 ◽  
pp. 349-353
Author(s):  
Jing Tang ◽  
En Xing Zheng
Keyword(s):  
Control System ◽  
Temperature Control ◽  
Temperature Sensor ◽  
Temperature Control System ◽  
Motor Speed ◽  
Temperature Index ◽  
Digital Temperature Sensor ◽  
Microcontroller Unit

The paper designs a temperature control system based on AT89C51 and DS18B20. The design uses the DS18B20 digital temperature sensor as the temperature acquisition unit and the AT89C51 microcontroller unit to control them, not only have the advantages that easy to control and with good flexibility, but also can greatly enhance the controlled temperature index.

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