Improved dynamic performance of direct torque control at low speed over a scalar control

2013 ◽  
Author(s):  
N. Venkataramana Naik ◽  
S. P. Singh
Keyword(s):  
Dynamic Performance ◽  
Direct Torque Control ◽  
Torque Control ◽  
Low Speed ◽  
Scalar Control

scholarly journals Stator Flux Observer for Induction Motor Based on Tracking Differentiator

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Dafang Wang ◽  
Zhenfei Hu ◽  
Cheng Zhu ◽  
Chuanwei Zhou ◽  
Yajing Xie
Keyword(s):  
Dynamic Error ◽  
Dynamic Performance ◽  
Direct Torque Control ◽  
Torque Control ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Speed ◽  
Tracking Differentiator ◽  
Low Pass ◽  
Stator Flux

Voltage model is commonly used in direct torque control (DTC) for flux observing of asynchronous motor. In order to improve low-speed and dynamic performance of the voltage model, a modified low-pass filter (LPF) algorithm is proposed. Firstly, the tracking differentiator is brought in to modulate the measured stator current, which suppresses the measurement noise, and then amplitude and phase compensation is made towards the stator electromotive force (EMF), after which the stator flux is obtained through a low-pass filter. This method can eliminate the dynamic error of flux filtered by LPF and improve low-speed performance. Experimental results demonstrate effectiveness and improved dynamic performance of such method.

Direct Torque Control of the Genetic Neural Network under the Low-Speed

2012 ◽  
Vol 466-467 ◽  
pp. 694-697
Author(s):  
Lian Zhang ◽  
Wei Lai ◽  
Jie Li
Keyword(s):  
Neural Network ◽  
Structure Learning ◽  
Dynamic Performance ◽  
Asynchronous Motor ◽  
Direct Torque Control ◽  
Optimal Solution ◽  
Torque Control ◽  
Bp Network ◽  
Low Speed ◽  
Genetic Neural Network

For the direct torque control of asynchronous motor rapid response and speed ripple, this article proposes the genetic neural network algorithm based on the model of stator flux, to achieve the selecting of switch state under the low-speed. Using the global optimization and search method of genetic algorithm obtains global optimal solution, while the connection weights and network structure learning improve the training effectiveness of neural network, so that the BP network has better adaptive characteristic. The effectiveness of the design is verified by the simulation, and it shows that the speed control system has good dynamic performance and steady state performance under the low-speed.

A Direct Torque Control Driven Vessel Actuator Device

2014 ◽  
Vol 651-653 ◽  
pp. 593-597
Author(s):  
Hui Lue Jiang ◽  
Bo Liu ◽  
Chuan Dao Liu
Keyword(s):  
Dynamic Performance ◽  
Complex Structure ◽  
Direct Torque Control ◽  
Torque Ripple ◽  
Torque Control ◽  
Low Speed ◽  
Simulation Results ◽  
Low Efficiency ◽  
The Impact

Actuator is one of the most important auxiliary mechanisms used to control the ship heading. Focused on the existed shortages of conventional hydraulic driven vessel actuator as complex structure, low efficiency and response etc, by the analysis of torque variation to access the impact of direct torque control and design an actuator used direct torque control of which is simple and easy to implement. Simulation results show that this scheme can reduce system without dynamic performance, low-speed operation to expand the scope of the system, reducing the torque ripple, while improving the low-speed torque of the motor.

Study of the Electricity-Draw Control System in Electrical Engineering Based on Neural Network DTC

2013 ◽  
Vol 676 ◽  
pp. 209-212
Author(s):  
Lu Huan Shi ◽  
Yao Hui Li
Keyword(s):  
Neural Network ◽  
Control System ◽  
Control Strategy ◽  
Dynamic Performance ◽  
Asynchronous Motor ◽  
Sudden Change ◽  
Direct Torque Control ◽  
Torque Control ◽  
Electric Locomotive ◽  
Low Velocity

In the electricity draws control system, the change of Low-velocity area of Rs will bring about a series of problem, especially the stator current and flux, will cause the distortion of the speed pulse vibration. The test discussed control scheme and optimization designs of asynchronous draw motors from exchange transmission electric locomotive operation characteristic demand. It adopts control strategy of neural network direct torque control (DTC) to control electricity draw the locomotive, to analyze the reacting of starting and sudden change of load, verifying this method may effectively improve the dynamic performance of the asynchronous motor, got up the very good inhibitory action to the low speed area torque pulsation. Thus the simulation results have proven the neural network DTC control strategy feasibility.

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