Description: 基于模糊神经白适应的感应电动机直接转矩控制研究，希望对大家有用。-White adaptation based on fuzzy neural induction motor direct torque control study in the hope that useful to everyone. Platform: |
Size: 2462720 |
Author:王大钊 |
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Description: 该仿真模型是一种利用模糊控制器调节PWM信号占空比的异步电动机直接转矩控制的策略，即在传统异步电动机直接转矩控制的基础上，用模糊控制器代替传统DTC中的滞环比较器和空间电压矢量状态选择器来细分控制规则，最后控制逆变器的开关，以减小转矩和磁链脉动，从而改善交流异步电机伺服系统的动、静态品质，使整个系统具有较强的鲁棒性和自适应性。-A method of the stator resistance estimate which based on the fuzzy neural network was proposed and the motor speed is estimated by MRAS speed identification algorithm based on the stator voltage and the current that can be easily detected. Besides, a new design of fuzzy direct torque control system of induction motor was introduced in this paper, which based on strategy of modulating the duty cycle to decrease the torque and stator flux ripple. This design uses fuzzy control block to instead of the traditional space voltage vector selector to control the inverter switch which can improve the static and dynamic performances of AC asynchronous motors, which make the whole control system have strong robustness. Platform: |
Size: 14336 |
Author:王晨 |
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Description: In This paper, the authors propose a Sensorless Direct Torque and Flux Control (DTFC) of
Induction Motor (IM) using two approach intelligent techniques: Mamdani Fuzzy Logic (FL)
controller is used for controlling the rotor speed and Artificial Neural Network (ANN) applied in
switching select stator voltage. We estimated the rotor speed by using the Model Reference
Adaptive Systems (MRAS). The control method proposed in this paper can reduce the torque,
stator flux and current ripples and especially improve system good dynamic performance and
robustness in high and low speeds-In This paper, the authors propose a Sensorless Direct Torque and Flux Control (DTFC) of
Induction Motor (IM) using two approach intelligent techniques: Mamdani Fuzzy Logic (FL)
controller is used for controlling the rotor speed and Artificial Neural Network (ANN) applied in
switching select stator voltage. We estimated the rotor speed by using the Model Reference
Adaptive Systems (MRAS). The control method proposed in this paper can reduce the torque,
stator flux and current ripples and especially improve system good dynamic performance and
robustness in high and low speeds.. Platform: |
Size: 3107840 |
Author:aa |
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Search - direct torque control fuzzy neural