Based on analysis of the current congesting algorithm, a new congesting control mechanism is proposed, which employs SELA (stochastic estimator learning algorithm) and fuzzy logic controller.
在分析了目前的拥塞控制算法的基础上，将随机估计学习算法(SELA)和模糊逻辑的知识引入拥塞控制，提出了新的拥塞控制模型。
The method includes three modules: fuzzy equivalent interference estimator, neural network interference predictor, and fuzzy call admission processor.
包括三个模块：模糊等效干扰估计器、神经网络干扰预测器以及模糊呼叫接纳处理器。
Simulation results show that this fuzzy-neural network estimator can precisely measure the value of resistance and improve the low-speed performances of DTC system efficiently.
仿真结果表明了模糊神经网络观测器可实现对定子电阻的精确检测，从而提高直接转矩控制系统的低速性能。
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