Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training a...Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.展开更多
This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different he...This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.展开更多
AC motors, especially the squirrel cage induction motors have the advantages of simple structure, good reliability and low cost. They are more suitable to be used as electrical dynamometers to provide dynamic load for...AC motors, especially the squirrel cage induction motors have the advantages of simple structure, good reliability and low cost. They are more suitable to be used as electrical dynamometers to provide dynamic load for bench test systems. But, the speed and torque of induction motors are not easy to be controlled accurately. In this work, an electrical dynamometer based on the induction motor is proposed. In order to get better control performance of torque and speed of induction motor, an improved direct torque control method(DTC) is also developed based on the space vector modulation(SVM) technique. The performance of the proposed dynamometer system is validated in the Matlab/Simulink platform. The simulation results show that the new dynamometer has good torque and stator flux response. And the torque and stator current ripples of it are reduced significantly compared with using the conventional DTC method.展开更多
基金the National Natural Science Foundation of China (60374032).
文摘Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.
基金Project supported by Faculty of Technology,Department of Electrical Engineering,University of Batna,Algeria
文摘This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.
基金Project(SS2012AA04104)supported by High-tech Research and Development Program of China
文摘AC motors, especially the squirrel cage induction motors have the advantages of simple structure, good reliability and low cost. They are more suitable to be used as electrical dynamometers to provide dynamic load for bench test systems. But, the speed and torque of induction motors are not easy to be controlled accurately. In this work, an electrical dynamometer based on the induction motor is proposed. In order to get better control performance of torque and speed of induction motor, an improved direct torque control method(DTC) is also developed based on the space vector modulation(SVM) technique. The performance of the proposed dynamometer system is validated in the Matlab/Simulink platform. The simulation results show that the new dynamometer has good torque and stator flux response. And the torque and stator current ripples of it are reduced significantly compared with using the conventional DTC method.
